From 2470dc4034021366a0b0e799c557783f98bc95d3 Mon Sep 17 00:00:00 2001 From: jon-hagg <66005238+jon-hagg@users.noreply.github.com> Date: Fri, 26 Mar 2021 12:18:56 -0700 Subject: [PATCH 01/61] ci: add pep8-naming to flake8 and fix warnings (#157) --- prereise/gather/demanddata/eia/clean_data.py | 16 +++--- prereise/gather/solardata/nsrdb/sam.py | 2 +- prereise/gather/winddata/rap/power_curves.py | 50 +++++++++---------- .../winddata/rap/tests/test_power_curves.py | 30 +++++------ tox.ini | 1 + 5 files changed, 50 insertions(+), 49 deletions(-) diff --git a/prereise/gather/demanddata/eia/clean_data.py b/prereise/gather/demanddata/eia/clean_data.py index aca83ec9c..d1b84c76d 100644 --- a/prereise/gather/demanddata/eia/clean_data.py +++ b/prereise/gather/demanddata/eia/clean_data.py @@ -192,15 +192,15 @@ def replace_with_shifted_demand(demand, start, end): # Attempt to shift demand data, # getting progressively more aggressive if necessary filled_demand = pd.DataFrame(index=demand.index) - for baName in demand.columns: - shifted_demand_ba = shifted_demand.loc[:, [baName, "dayofweek"]] - shifted_demand_ba.columns = [baName] + column_names - shifted_demand_ba[baName] = fill_ba_demand(shifted_demand_ba, baName, day_map) - shifted_demand_ba[baName] = fill_ba_demand( - shifted_demand_ba, baName, more_days_map + for ba_name in demand.columns: + shifted_demand_ba = shifted_demand.loc[:, [ba_name, "dayofweek"]] + shifted_demand_ba.columns = [ba_name] + column_names + shifted_demand_ba[ba_name] = fill_ba_demand(shifted_demand_ba, ba_name, day_map) + shifted_demand_ba[ba_name] = fill_ba_demand( + shifted_demand_ba, ba_name, more_days_map ) - filled_demand[baName] = fill_ba_demand( - shifted_demand_ba, baName, more_more_days_map + filled_demand[ba_name] = fill_ba_demand( + shifted_demand_ba, ba_name, more_more_days_map ) return filled_demand diff --git a/prereise/gather/solardata/nsrdb/sam.py b/prereise/gather/solardata/nsrdb/sam.py index 3262a9001..4646d6773 100644 --- a/prereise/gather/solardata/nsrdb/sam.py +++ b/prereise/gather/solardata/nsrdb/sam.py @@ -1,7 +1,7 @@ import numpy as np import pandas as pd import PySAM.Pvwattsv7 as PVWatts -import PySAM.PySSC as pssc +import PySAM.PySSC as pssc # noqa: N813 from powersimdata.network.usa_tamu.constants.zones import ( abv2interconnect, id2abv, diff --git a/prereise/gather/winddata/rap/power_curves.py b/prereise/gather/winddata/rap/power_curves.py index e5b9ba2ac..211a7fdeb 100644 --- a/prereise/gather/winddata/rap/power_curves.py +++ b/prereise/gather/winddata/rap/power_curves.py @@ -28,13 +28,13 @@ def _shift_turbine_curve(turbine_curve, hub_height, maxspd, new_curve_res): return shifted_curve -def build_state_curves(Form860, PowerCurves, maxspd=30, default="IEC class 2", rsd=0): +def build_state_curves(form_860, power_curves, maxspd=30, default="IEC class 2", rsd=0): """Parse Form 860 and turbine curves to obtain average state curves. - :param pandas.DataFrame Form860: EIA Form 860 data. - :param pandas.DataFrame PowerCurves: turbine power curves. + :param pandas.DataFrame form_860: EIA Form 860 data. + :param pandas.DataFrame power_curves: turbine power curves. :param float maxspd: maximum x value for state curves. - :param str default: turbine curve name for turbines not in PowerCurves. + :param str default: turbine curve name for turbines not in power_curves. :param float rsd: relative standard deviation for spatiotemporal smoothing. :return: (*pandas.DataFrame*) - DataFrame of state curves. """ @@ -45,13 +45,13 @@ def build_state_curves(Form860, PowerCurves, maxspd=30, default="IEC class 2", r hubheight_col = "Turbine Hub Height (Feet)" new_curve_res = 0.01 # resolution: m/s - states = Form860["State"].unique() + states = form_860["State"].unique() curve_x = np.arange(0, maxspd + new_curve_res, new_curve_res) state_curves = pd.DataFrame(curve_x, columns=["Speed bin (m/s)"]) for s in states: cumulative_curve = np.zeros_like(curve_x) cumulative_capacity = 0 - state_wind_farms = Form860[Form860["State"] == s] + state_wind_farms = form_860[form_860["State"] == s] for i, f in enumerate(state_wind_farms.index): # Look up attributes from Form 860 farm_capacity = state_wind_farms[capacity_col].iloc[i] @@ -60,9 +60,9 @@ def build_state_curves(Form860, PowerCurves, maxspd=30, default="IEC class 2", r turbine_model = state_wind_farms[model_col].iloc[i] # Look up turbine-specific power curve (or default) turbine_name = " ".join([turbine_mfg, turbine_model]) - if turbine_name not in PowerCurves.columns: + if turbine_name not in power_curves.columns: turbine_name = default - turbine_curve = PowerCurves[turbine_name] + turbine_curve = power_curves[turbine_name] # Shift based on farm-specific hub height shifted_curve = _shift_turbine_curve( turbine_curve, hub_height, maxspd, new_curve_res @@ -76,7 +76,7 @@ def build_state_curves(Form860, PowerCurves, maxspd=30, default="IEC class 2", r # Add an 'Offshore' state with a representative curve hub_height = 393.701 # 120 meters, in feet to match Form860 data - turbine_curve = PowerCurves["Vestas V164-8.0"] + turbine_curve = power_curves["Vestas V164-8.0"] shifted_curve = _shift_turbine_curve( turbine_curve, hub_height, maxspd, new_curve_res ) @@ -139,24 +139,24 @@ def get_form_860(data_dir, year=2016): return form_860 -def get_power(PowerCurves, StatePowerCurves, wspd, turbine, default="IEC class 2"): +def get_power(power_curves, state_power_curves, wspd, turbine, default="IEC class 2"): """Convert wind speed to power using NREL turbine power curves. - :param pandas.DataFrame PowerCurves: turbine power curves data. - :param pandas.DataFrame StatePowerCurves: state average power curves data. + :param pandas.DataFrame power_curves: turbine power curves data. + :param pandas.DataFrame state_power_curves: state average power curves data. :param float wspd: wind speed (in m/s). :param str default: default turbine name. :param str turbine: turbine name, IEC class, or state code for average. :return: (*float*) -- normalized power. """ - if turbine in StatePowerCurves.columns: - curve = StatePowerCurves[turbine] + if turbine in state_power_curves.columns: + curve = state_power_curves[turbine] else: try: - curve = PowerCurves[turbine] + curve = power_curves[turbine] except KeyError: print(turbine, "not found, defaulting to", default) - curve = PowerCurves[default] + curve = power_curves[default] return np.interp(wspd, curve.index.values, curve.values, left=0, right=0) @@ -167,9 +167,9 @@ def get_turbine_power_curves(filename="PowerCurves.csv"): :return: (*pandas.DataFrame*) -- normalized turbine power curves. """ powercurves_path = path.join(data_dir, filename) - PowerCurves = pd.read_csv(powercurves_path, index_col=0, header=None).T - PowerCurves.set_index("Speed bin (m/s)", inplace=True) - return PowerCurves + power_curves = pd.read_csv(powercurves_path, index_col=0, header=None).T + power_curves.set_index("Speed bin (m/s)", inplace=True) + return power_curves def get_state_power_curves(filename="StatePowerCurves.csv", rsd=0.4): @@ -180,12 +180,12 @@ def get_state_power_curves(filename="StatePowerCurves.csv", rsd=0.4): :param float rsd: relative standard deviation, for wind speed distribution. :return: (*pandas.DataFrame*) -- normalized state power curves. """ - PowerCurves = get_turbine_power_curves() - Form860 = get_form_860(data_dir) + power_curves = get_turbine_power_curves() + form_860 = get_form_860(data_dir) statepowercurves_path = path.join(data_dir, filename) try: - StatePowerCurves = pd.read_csv(statepowercurves_path, index_col=0) + state_power_curves = pd.read_csv(statepowercurves_path, index_col=0) except FileNotFoundError: - StatePowerCurves = build_state_curves(Form860, PowerCurves, rsd=rsd) - StatePowerCurves.to_csv(statepowercurves_path) - return StatePowerCurves + state_power_curves = build_state_curves(form_860, power_curves, rsd=rsd) + state_power_curves.to_csv(statepowercurves_path) + return state_power_curves diff --git a/prereise/gather/winddata/rap/tests/test_power_curves.py b/prereise/gather/winddata/rap/tests/test_power_curves.py index ec405ee32..c93acb5a3 100644 --- a/prereise/gather/winddata/rap/tests/test_power_curves.py +++ b/prereise/gather/winddata/rap/tests/test_power_curves.py @@ -53,7 +53,7 @@ def setUp(self): self.form_860 = form_860 def test_build_state_curves(self): - PowerCurves = get_turbine_power_curves() + power_curves = get_turbine_power_curves() maxspd = 25 new_curve_res = 0.01 expected_length = math.ceil(maxspd / new_curve_res) + 1 @@ -61,7 +61,7 @@ def test_build_state_curves(self): expected_states = list(self.form_860["State"].unique()) + ["Offshore"] expected_shape = (expected_length, len(expected_states)) - state_curves = build_state_curves(self.form_860, PowerCurves, maxspd) + state_curves = build_state_curves(self.form_860, power_curves, maxspd) self.assertIsInstance(state_curves, pd.DataFrame) self.assertEqual(state_curves.index.name, "Speed bin (m/s)") @@ -71,7 +71,7 @@ def test_build_state_curves(self): self.assertEqual(set(expected_states), set(state_curves.columns)) # Make sure California got shifted (lower cutoff from full capacity) - original = PowerCurves["Vestas V80-1.8"] + original = power_curves["Vestas V80-1.8"] self.assertTrue(_last_one(state_curves["CA"]) < _last_one(original)) # Make sure 'Toyota Corolla' deaults to 'IEC class 2' @@ -83,8 +83,8 @@ def test_build_state_curves(self): # (i.e. crazy tall wind farm with 0 capacity doesn't matter) original = np.interp( state_curves.index.to_numpy(), - PowerCurves["GE 1.5 S"].index.to_numpy(), - PowerCurves["GE 1.5 S"].to_numpy(), + power_curves["GE 1.5 S"].index.to_numpy(), + power_curves["GE 1.5 S"].to_numpy(), ) assert_array_almost_equal(state_curves["NY"].to_numpy(), original) assert_array_almost_equal(state_curves["NY"].to_numpy(), original) @@ -98,7 +98,7 @@ def test_build_state_curves(self): class TestShiftTurbineCurve(unittest.TestCase): def setUp(self): - self.PowerCurves = get_turbine_power_curves() + self.power_curves = get_turbine_power_curves() def _check_curve_structure(self, shifted_curve, maxspd, new_curve_res): expected_length = math.ceil(maxspd / new_curve_res) + 1 @@ -110,7 +110,7 @@ def _check_curve_structure(self, shifted_curve, maxspd, new_curve_res): self.assertEqual(shifted_curve.to_numpy().shape, (expected_length,)) def test_shift_turbine_curve_higher_hub(self): - original = self.PowerCurves["IEC class 2"] + original = self.power_curves["IEC class 2"] shifted = _shift_turbine_curve( original, hub_height=270, maxspd=26, new_curve_res=0.01 ) @@ -119,7 +119,7 @@ def test_shift_turbine_curve_higher_hub(self): self.assertTrue(_last_one(shifted) < _last_one(original)) def test_shift_turbine_curve_lower_hub(self): - original = self.PowerCurves["IEC class 2"] + original = self.power_curves["IEC class 2"] shifted = _shift_turbine_curve( original, hub_height=260, maxspd=29, new_curve_res=0.02 ) @@ -128,7 +128,7 @@ def test_shift_turbine_curve_lower_hub(self): self.assertTrue(_last_one(shifted) > _last_one(original)) def test_shift_turbine_curve_sameheight_hub(self): - original = self.PowerCurves["IEC class 2"] + original = self.power_curves["IEC class 2"] shifted = _shift_turbine_curve( original, hub_height=262.467, maxspd=30, new_curve_res=0.05 ) @@ -209,13 +209,13 @@ def test_year_str(self): class TestGetTurbinePowerCurves(unittest.TestCase): def test_get_turbine_power_curves(self): - PowerCurves = get_turbine_power_curves() - self.assertIsInstance(PowerCurves, pd.DataFrame) - self.assertEqual(PowerCurves.index.name, "Speed bin (m/s)") + power_curves = get_turbine_power_curves() + self.assertIsInstance(power_curves, pd.DataFrame) + self.assertEqual(power_curves.index.name, "Speed bin (m/s)") class TestGetStatePowerCurves(unittest.TestCase): def test_get_state_power_curves(self): - StatePowerCurves = get_state_power_curves() - self.assertIsInstance(StatePowerCurves, pd.DataFrame) - self.assertEqual(StatePowerCurves.index.name, "Speed bin (m/s)") + state_power_curves = get_state_power_curves() + self.assertIsInstance(state_power_curves, pd.DataFrame) + self.assertEqual(state_power_curves.index.name, "Speed bin (m/s)") diff --git a/tox.ini b/tox.ini index e5fc6c5f1..56d5b50cd 100644 --- a/tox.ini +++ b/tox.ini @@ -11,6 +11,7 @@ deps = {format,checkformatting}: black {format,checkformatting}: isort flake8: flake8 + flake8: pep8-naming commands = pytest: pipenv sync --dev local: pytest -m 'not integration' From 03db0e07d15ce1414d23b2d3b3065acc7c3f2958 Mon Sep 17 00:00:00 2001 From: jon-hagg <66005238+jon-hagg@users.noreply.github.com> Date: Mon, 29 Mar 2021 16:11:26 -0700 Subject: [PATCH 02/61] Update dependencies (#158) Co-authored-by: jon-hagg --- Pipfile.lock | 400 ++++++++++++++++++++++++--------------------------- 1 file changed, 188 insertions(+), 212 deletions(-) diff --git a/Pipfile.lock b/Pipfile.lock index 0afe9726f..5714bceee 100644 --- a/Pipfile.lock +++ b/Pipfile.lock @@ -14,14 +14,6 @@ ] }, "default": { - "atomicwrites": { - "hashes": [ - "sha256:6d1784dea7c0c8d4a5172b6c620f40b6e4cbfdf96d783691f2e1302a7b88e197", - "sha256:ae70396ad1a434f9c7046fd2dd196fc04b12f9e91ffb859164193be8b6168a7a" - ], - "markers": "sys_platform == 'win32'", - "version": "==1.4.0" - }, "attrs": { "hashes": [ "sha256:31b2eced602aa8423c2aea9c76a724617ed67cf9513173fd3a4f03e3a929c7e6", @@ -147,26 +139,23 @@ ], "version": "==3.0.4" }, - "colorama": { - "hashes": [ - "sha256:5941b2b48a20143d2267e95b1c2a7603ce057ee39fd88e7329b0c292aa16869b", - "sha256:9f47eda37229f68eee03b24b9748937c7dc3868f906e8ba69fbcbdd3bc5dc3e2" - ], - "markers": "sys_platform == 'win32'", - "version": "==0.4.4" - }, "cryptography": { "hashes": [ - "sha256:0bf49d5b38e4f3745a0eab0597fa97720dd49b30d65f534b49a82e303f149deb", - "sha256:18d6f3ac1da14a01c95f4590ee58e96aa6628d231ce738e9eca330b9997127b6", - "sha256:4f6761a82b51fe02cda8f45af1c2f698a10f50003dc9c2572d8a49eda2e6d35b", - "sha256:8b3b79af57e12aabbc3db81e563eaa07870293a1ffdcc891d107035ce9a0dbff", - 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prereise/gather/__init__.py | 8 -------- prereise/gather/demanddata/__init__.py | 1 - prereise/gather/demanddata/eia/__init__.py | 1 - prereise/gather/demanddata/eia/tests/__init__.py | 1 - prereise/gather/hydrodata/__init__.py | 1 - prereise/gather/hydrodata/eia/__init__.py | 6 ------ prereise/gather/solardata/__init__.py | 1 - prereise/gather/solardata/ga_wind/__init__.py | 1 - prereise/gather/solardata/nsrdb/__init__.py | 1 - prereise/gather/solardata/nsrdb/tests/__init__.py | 1 - prereise/gather/solardata/tests/__init__.py | 1 - prereise/gather/tests/__init__.py | 6 ------ prereise/gather/winddata/__init__.py | 1 - prereise/gather/winddata/rap/__init__.py | 1 - 15 files changed, 32 deletions(-) diff --git a/prereise/__init__.py b/prereise/__init__.py index bf3839b55..e69de29bb 100644 --- a/prereise/__init__.py +++ b/prereise/__init__.py @@ -1 +0,0 @@ -__all__ = ["gather"] diff --git a/prereise/gather/__init__.py b/prereise/gather/__init__.py index 758f5c89a..e69de29bb 100644 --- a/prereise/gather/__init__.py +++ b/prereise/gather/__init__.py @@ -1,8 +0,0 @@ -__all__ = [ - "demanddata", - "helpers", - "hydrodata", - "request_util", - "solardata", - "winddata", -] diff --git a/prereise/gather/demanddata/__init__.py b/prereise/gather/demanddata/__init__.py index a00cd0e91..e69de29bb 100644 --- a/prereise/gather/demanddata/__init__.py +++ b/prereise/gather/demanddata/__init__.py @@ -1 +0,0 @@ -__all__ = ["eia", "nrel_efs"] diff --git a/prereise/gather/demanddata/eia/__init__.py b/prereise/gather/demanddata/eia/__init__.py index 83372332c..e69de29bb 100644 --- a/prereise/gather/demanddata/eia/__init__.py +++ b/prereise/gather/demanddata/eia/__init__.py @@ -1 +0,0 @@ -__all__ = ["clean_data", "get_eia_data", "map_ba"] diff --git a/prereise/gather/demanddata/eia/tests/__init__.py b/prereise/gather/demanddata/eia/tests/__init__.py index 8ef9f6427..e69de29bb 100644 --- a/prereise/gather/demanddata/eia/tests/__init__.py +++ b/prereise/gather/demanddata/eia/tests/__init__.py @@ -1 +0,0 @@ -__all__ = ["test_clean_data", "test_get_eia_data", "test_map_ba"] diff --git a/prereise/gather/hydrodata/__init__.py b/prereise/gather/hydrodata/__init__.py index b6602d864..e69de29bb 100644 --- a/prereise/gather/hydrodata/__init__.py +++ b/prereise/gather/hydrodata/__init__.py @@ -1 +0,0 @@ -__all__ = ["eia"] diff --git a/prereise/gather/hydrodata/eia/__init__.py b/prereise/gather/hydrodata/eia/__init__.py index 1993b1973..e69de29bb 100644 --- a/prereise/gather/hydrodata/eia/__init__.py +++ b/prereise/gather/hydrodata/eia/__init__.py @@ -1,6 +0,0 @@ -__all__ = [ - "decompose_profile", - "helpers", - "interpolate_capacity_factors", - "net_demand", -] diff --git a/prereise/gather/solardata/__init__.py b/prereise/gather/solardata/__init__.py index 08104e2d3..e69de29bb 100644 --- a/prereise/gather/solardata/__init__.py +++ b/prereise/gather/solardata/__init__.py @@ -1 +0,0 @@ -__all__ = ["constants", "helpers", "pv_tracking", "ga_wind", "nsrdb", "tests"] diff --git a/prereise/gather/solardata/ga_wind/__init__.py b/prereise/gather/solardata/ga_wind/__init__.py index 6510832fb..e69de29bb 100644 --- a/prereise/gather/solardata/ga_wind/__init__.py +++ b/prereise/gather/solardata/ga_wind/__init__.py @@ -1 +0,0 @@ -__all__ = ["helpers", "ga_wind"] diff --git a/prereise/gather/solardata/nsrdb/__init__.py b/prereise/gather/solardata/nsrdb/__init__.py index 3d1c5013d..e69de29bb 100644 --- a/prereise/gather/solardata/nsrdb/__init__.py +++ b/prereise/gather/solardata/nsrdb/__init__.py @@ -1 +0,0 @@ -__all__ = ["naive", "sam", "nrel_api"] diff --git a/prereise/gather/solardata/nsrdb/tests/__init__.py b/prereise/gather/solardata/nsrdb/tests/__init__.py index bdf9c34a4..e69de29bb 100644 --- a/prereise/gather/solardata/nsrdb/tests/__init__.py +++ b/prereise/gather/solardata/nsrdb/tests/__init__.py @@ -1 +0,0 @@ -__all__ = ["test_nrel_api"] diff --git a/prereise/gather/solardata/tests/__init__.py b/prereise/gather/solardata/tests/__init__.py index 5d61828a9..e69de29bb 100644 --- a/prereise/gather/solardata/tests/__init__.py +++ b/prereise/gather/solardata/tests/__init__.py @@ -1 +0,0 @@ -__all__ = ["mock_pv_info", "test_pv_tracking"] diff --git a/prereise/gather/tests/__init__.py b/prereise/gather/tests/__init__.py index 6352de78c..e69de29bb 100644 --- a/prereise/gather/tests/__init__.py +++ b/prereise/gather/tests/__init__.py @@ -1,6 +0,0 @@ -__all__ = [ - "mock_generation_data_frame", - "test_get_monthly_net_generation", - "test_rate_limit", - "test_retry", -] diff --git a/prereise/gather/winddata/__init__.py b/prereise/gather/winddata/__init__.py index 03a092f32..e69de29bb 100644 --- a/prereise/gather/winddata/__init__.py +++ b/prereise/gather/winddata/__init__.py @@ -1 +0,0 @@ -__all__ = ["rap"] diff --git a/prereise/gather/winddata/rap/__init__.py b/prereise/gather/winddata/rap/__init__.py index 8337340e7..e69de29bb 100644 --- a/prereise/gather/winddata/rap/__init__.py +++ b/prereise/gather/winddata/rap/__init__.py @@ -1 +0,0 @@ -__all__ = ["helpers", "impute", "rap", "noaa_api"] From df76740c43d9df55e4eb4405e9204a5f0dfd67ba Mon Sep 17 00:00:00 2001 From: Ben RdO Date: Wed, 28 Apr 2021 09:14:13 -0700 Subject: [PATCH 04/61] chore: create bug report issue template (#162) --- .github/ISSUE_TEMPLATE/bug_report.md | 47 ++++++++++++++++++++++++++++ 1 file changed, 47 insertions(+) create mode 100644 .github/ISSUE_TEMPLATE/bug_report.md diff --git a/.github/ISSUE_TEMPLATE/bug_report.md b/.github/ISSUE_TEMPLATE/bug_report.md new file mode 100644 index 000000000..451b4de3e --- /dev/null +++ b/.github/ISSUE_TEMPLATE/bug_report.md @@ -0,0 +1,47 @@ +--- +name: Bug report +about: Create a report to help us improve +title: Bug report +labels: bug +assignees: ahurli, BainanXia, danielolsen, jon-hagg, rouille + +--- + +# :beetle: + +- [ ] I have checked that this issue has not already been reported. + + +### Bug summary +A short 1-2 sentences that succinctly describes the bug. + +### Code for reproduction +A minimum code snippet required to reproduce the bug. Please make sure to minimize the +number of dependencies required. +```python +# Paste your code here +# +# +``` + +### Actual outcome +The output produced by the above code, which may be a screenshot, console output, etc. +```shell +# If applicable, paste the console output here +# +# +``` + +### Expected outcome +A description of the expected outcome from the code snippet. + +### Environment +Please specify your platform and versions of the relevant libraries you are using: +* Operating system: +* PreREISE revision (run `git rev-parse origin/HEAD`): +* Python version: +* Jupyter version (if applicable): +* Other libraries: + +### Additional context +Add any other context about the problem here. From 4b78623145ff1e3bed9192b65b0db85a6d2c5320 Mon Sep 17 00:00:00 2001 From: jon-hagg <66005238+jon-hagg@users.noreply.github.com> Date: Fri, 30 Apr 2021 10:57:35 -0700 Subject: [PATCH 05/61] ci: add coverage report to pytest (#163) --- .coveragerc | 6 + .github/workflows/test.yml | 1 + Pipfile | 6 +- Pipfile.lock | 439 ++++++++++++++++++++----------------- pytest.ini | 1 + requirements.txt | 8 +- 6 files changed, 252 insertions(+), 209 deletions(-) create mode 100644 .coveragerc diff --git a/.coveragerc b/.coveragerc new file mode 100644 index 000000000..ac59cf57c --- /dev/null +++ b/.coveragerc @@ -0,0 +1,6 @@ +[run] +branch = True +omit = + **/test_*.py + **/__init__.py + diff --git a/.github/workflows/test.yml b/.github/workflows/test.yml index 49ba23ffa..0fbe2aa23 100644 --- a/.github/workflows/test.yml +++ b/.github/workflows/test.yml @@ -12,6 +12,7 @@ jobs: runs-on: ubuntu-latest strategy: + fail-fast: false matrix: python-version: [3.7, 3.8] diff --git a/Pipfile b/Pipfile index 2c47ce445..1bdb53f6a 100644 --- a/Pipfile +++ b/Pipfile @@ -5,6 +5,9 @@ verify_ssl = true [dev-packages] black = "*" +pytest = "*" +coverage = "*" +pytest-cov = "*" [packages] bokeh = "==2.0.2" @@ -12,7 +15,6 @@ h5pyd = "==0.3.3" matplotlib = "~=3.3" numpy = "~=1.19" pandas = "~=1.1.2" -pytest = "==5.4.3" python-dateutil = "==2.7.5" requests = "~=2.24.0" scipy = "==1.4.1" @@ -20,5 +22,5 @@ tqdm = "==4.29.1" xlrd = "==1.2.0" netCDF4 = "==1.5.4" powersimdata = {editable = true, path = "../PowerSimData"} -nrel-pysam = "~=2.1.4" +nrel-pysam = "~=2.2" pyproj = "==2.6.1.post1" diff --git a/Pipfile.lock b/Pipfile.lock index 5714bceee..a55ded553 100644 --- a/Pipfile.lock +++ b/Pipfile.lock @@ -1,7 +1,7 @@ { "_meta": { "hash": { - "sha256": "c1945dc1a9d2fb0c974c361d5fc371f6d7bf74472689c54f39e6dfa9a5e86f55" + "sha256": "99a0ccf964c137594bf784b32bc43083069964145135b9614874d8421964aba6" }, "pipfile-spec": 6, "requires": {}, @@ -14,14 +14,6 @@ ] }, "default": { - "attrs": { - "hashes": [ - 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tqdm==4.29.1 xlrd==1.2.0 -nrel-pysam~=2.1.4 +nrel-pysam~=2.2 +black +pytest +coverage +pytest-cov From ec5c2734ad2ddae54dd9656df95ef68f42e936d9 Mon Sep 17 00:00:00 2001 From: Ben RdO Date: Thu, 6 May 2021 14:14:12 -0700 Subject: [PATCH 06/61] chore: create feature request issue template (#165) --- .github/ISSUE_TEMPLATE/feature_request.md | 36 +++++++++++++++++++++++ 1 file changed, 36 insertions(+) create mode 100644 .github/ISSUE_TEMPLATE/feature_request.md diff --git a/.github/ISSUE_TEMPLATE/feature_request.md b/.github/ISSUE_TEMPLATE/feature_request.md new file mode 100644 index 000000000..eed038089 --- /dev/null +++ b/.github/ISSUE_TEMPLATE/feature_request.md @@ -0,0 +1,36 @@ +--- +name: Feature request +about: Suggest an idea for this project +title: Feature request +labels: feature request +assignees: ahurli, BainanXia, danielolsen, jon-hagg, rouille + +--- + + # :rocket: + +- [ ] Is your feature request essential for your project? + + +### Describe the workflow you want to enable +A clear and concise description of what can be enhanced, e.g., "I wish I could do [...]" + +### Describe your proposed implementation +This should provide a description of the feature request, e.g.: +* "The class `Foo` should have a new method `bar` that allows to [...]" +* "Function `foo` needs a new arguments `bar` to set [...]" +* "Create a new function `foo` to calculate [...]" + +If applicable, try to write a docstring for the desired feature. To illustrate, if you would like to add a new function in a module, provide: +* the name of the function +* a description of the task accomplished by the function +* a list of the input and output parameters together with their types (e.g., `int`, + `str`, `pandas.DataFrame`, etc.) and a short description of its/their meaning + +### Describe alternatives you've considered, if relevant +This should provide a description of any alternative solutions or features you've +considered. + +### Additional context +Add any other context or screenshots in this section, e.g., a plot from an article you +believe would clearly communicate results. From 75d8215d436088b7b080279f5aaef3094b0e7e53 Mon Sep 17 00:00:00 2001 From: jon-hagg <66005238+jon-hagg@users.noreply.github.com> Date: Fri, 14 May 2021 11:50:39 -0700 Subject: [PATCH 07/61] Update dependencies (#166) Co-authored-by: jon-hagg --- Pipfile.lock | 260 ++++++++++++++++++++++----------------------------- 1 file changed, 112 insertions(+), 148 deletions(-) diff --git a/Pipfile.lock b/Pipfile.lock index a55ded553..051ed4069 100644 --- a/Pipfile.lock +++ b/Pipfile.lock @@ -174,11 +174,11 @@ }, "jinja2": { "hashes": [ - "sha256:03e47ad063331dd6a3f04a43eddca8a966a26ba0c5b7207a9a9e4e08f1b29419", - "sha256:a6d58433de0ae800347cab1fa3043cebbabe8baa9d29e668f1c768cb87a333c6" + "sha256:2f2de5285cf37f33d33ecd4a9080b75c87cd0c1994d5a9c6df17131ea1f049c6", + "sha256:ea8d7dd814ce9df6de6a761ec7f1cac98afe305b8cdc4aaae4e114b8d8ce24c5" ], - "markers": "python_version >= '2.7' and python_version not in '3.0, 3.1, 3.2, 3.3, 3.4'", - "version": "==2.11.3" + "markers": "python_version >= '3.6'", + "version": "==3.0.0" }, "kiwisolver": { "hashes": [ @@ -220,86 +220,68 @@ }, "markupsafe": { "hashes": [ - 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"sha256:671238a46e4df0f3498d1c3270e5deb9b32d25134c99b7d75370a68cfbe9b634", - "sha256:6ad9c7bdf517a808242b998ac20063c41532a570d088d77eec1ee12b0b5574bc" + "sha256:50bcad0a0b9c5a72c8e4e7c9855a3ad496ca6a881a3641b4260605450772c54b", + "sha256:91ef2131a9bd6be8f76f1f08eac5c5317221d6ad1e143ae03894b862e8976890" ], "index": "pypi", - "version": "==6.2.3" + "version": "==6.2.4" }, "pytest-cov": { "hashes": [ - "sha256:359952d9d39b9f822d9d29324483e7ba04a3a17dd7d05aa6beb7ea01e359e5f7", - "sha256:bdb9fdb0b85a7cc825269a4c56b48ccaa5c7e365054b6038772c32ddcdc969da" + "sha256:8535764137fecce504a49c2b742288e3d34bc09eed298ad65963616cc98fd45e", + "sha256:95d4933dcbbacfa377bb60b29801daa30d90c33981ab2a79e9ab4452c165066e" ], "index": "pypi", - "version": "==2.11.1" + "version": "==2.12.0" }, "regex": { "hashes": [ From f1f8f6cb2d9c074817ce594ec7b1c4f7b45e4106 Mon Sep 17 00:00:00 2001 From: George Tong Date: Wed, 2 Jun 2021 10:39:15 -0700 Subject: [PATCH 08/61] docs: update setup documentation (#167) --- .gitignore | 5 +++++ README.md | 10 ++++++++-- 2 files changed, 13 insertions(+), 2 deletions(-) diff --git a/.gitignore b/.gitignore index 40e44f1af..d9036429d 100644 --- a/.gitignore +++ b/.gitignore @@ -109,6 +109,8 @@ venv/ ENV/ env.bak/ venv.bak/ +bin/ +pyvenv.cfg # Spyder project settings .spyderproject @@ -140,3 +142,6 @@ Thumbs.db # Data prereise/gather/winddata/data/StatePowerCurves.csv + +# Jupyter Notebook +share/ \ No newline at end of file diff --git a/README.md b/README.md index 32e073f24..3d63d1404 100644 --- a/README.md +++ b/README.md @@ -14,10 +14,17 @@ guide can be found [here](https://breakthrough-energy.github.io/docs/). Here are the instructions to install the **PreREISE** package. We strongly recommend that you pick one of the following options. +**NOTE: you MUST have +[PowerSimData](https://github.com/Breakthrough-Energy/PowerSimData/) cloned in +a folder adjacent to your clone of PreREISE as the installation of packages +in requirements.txt depends on files in PowerSimData.** ### A. Using pipenv If not already done, install `pipenv` by following the instructions on their -[webpage](https://pipenv.pypa.io/en/latest/). Then run: +[webpage](https://pipenv.pypa.io/en/latest/). If running `pipenv` +does not work after installation, make sure you also followed steps +[here](https://pipenv.pypa.io/en/latest/install/#pragmatic-installation-of-pipenv) +that address modifying your PATH. Then run: ```bash pipenv sync pipenv shell @@ -25,7 +32,6 @@ pipenv shell in the root folder of the package. The first command will create a virtual environment and install the dependencies. The second command will activate the environment. - ### B. Using the ***requirements.txt*** file First create an environment using `venv` (more details [here](https://docs.python.org/3/library/venv.html)). Note that `venv` is included in From e95ff3c91f4da6cb3cd52f618b914bc286a46a5b Mon Sep 17 00:00:00 2001 From: jon-hagg <66005238+jon-hagg@users.noreply.github.com> Date: Wed, 2 Jun 2021 18:01:37 -0700 Subject: [PATCH 09/61] Update dependencies (#170) Co-authored-by: rouille --- Pipfile.lock | 368 ++++++++++++++++++++++++++------------------------- 1 file changed, 187 insertions(+), 181 deletions(-) diff --git a/Pipfile.lock b/Pipfile.lock index 051ed4069..b4e907ad3 100644 --- a/Pipfile.lock +++ b/Pipfile.lock @@ -36,22 +36,31 @@ }, "certifi": { "hashes": [ - "sha256:1a4995114262bffbc2413b159f2a1a480c969de6e6eb13ee966d470af86af59c", - "sha256:719a74fb9e33b9bd44cc7f3a8d94bc35e4049deebe19ba7d8e108280cfd59830" + "sha256:2bbf76fd432960138b3ef6dda3dde0544f27cbf8546c458e60baf371917ba9ee", + "sha256:50b1e4f8446b06f41be7dd6338db18e0990601dce795c2b1686458aa7e8fa7d8" ], - "version": "==2020.12.5" + "version": "==2021.5.30" }, "cffi": { "hashes": [ 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data --- prereise/gather/demanddata/nrel_efs/tests/test_get_efs_data.py | 2 ++ 1 file changed, 2 insertions(+) diff --git a/prereise/gather/demanddata/nrel_efs/tests/test_get_efs_data.py b/prereise/gather/demanddata/nrel_efs/tests/test_get_efs_data.py index 36540064b..77bc24bf5 100644 --- a/prereise/gather/demanddata/nrel_efs/tests/test_get_efs_data.py +++ b/prereise/gather/demanddata/nrel_efs/tests/test_get_efs_data.py @@ -2,6 +2,7 @@ import zipfile import pandas as pd +import pytest from pandas.testing import assert_frame_equal from powersimdata.network.usa_tamu.constants.zones import abv2state @@ -50,6 +51,7 @@ def test_check_path(): assert test_fpath == exp_fpath +@pytest.mark.integration def test_download_data(): try: # Download a file using _download_data From 05cd7667eb2c3c55be276b6a8de477a1025fe92b Mon Sep 17 00:00:00 2001 From: Ben RdO Date: Wed, 2 Jun 2021 18:00:48 -0700 Subject: [PATCH 11/61] test: update marker description --- pytest.ini | 3 +-- 1 file changed, 1 insertion(+), 2 deletions(-) diff --git a/pytest.ini b/pytest.ini index 5794e99c6..a1693da7d 100644 --- a/pytest.ini +++ b/pytest.ini @@ -2,5 +2,4 @@ addopts = --cov=prereise testpaths = prereise markers = - integration: marks tests that requires connection to the server and - download data (deselect with '-m "not integration"') + integration: marks tests that require external dependencies (deselect with '-m "not integration"') From 7e1a88927c52e8388a0bf9bf805ec74b7a427d49 Mon Sep 17 00:00:00 2001 From: George Tong Date: Mon, 21 Jun 2021 10:49:36 -0700 Subject: [PATCH 12/61] feat: add cli to download rap data (#168) --- README.md | 27 ++++ prereise/cli/__init__.py | 0 prereise/cli/constants.py | 1 + prereise/cli/data_sources.py | 138 ++++++++++++++++++ prereise/cli/download/__init__.py | 0 prereise/cli/download/download_manager.py | 28 ++++ prereise/cli/download/tests/__init__.py | 0 .../download/tests/test_download_manager.py | 48 ++++++ prereise/cli/helpers.py | 52 +++++++ prereise/cli/tests/__init__.py | 0 prereise/cli/tests/test_data_sources.py | 87 +++++++++++ prereise/cli/tests/test_helpers.py | 69 +++++++++ 12 files changed, 450 insertions(+) create mode 100644 prereise/cli/__init__.py create mode 100644 prereise/cli/constants.py create mode 100644 prereise/cli/data_sources.py create mode 100644 prereise/cli/download/__init__.py create mode 100644 prereise/cli/download/download_manager.py create mode 100644 prereise/cli/download/tests/__init__.py create mode 100644 prereise/cli/download/tests/test_download_manager.py create mode 100644 prereise/cli/helpers.py create mode 100644 prereise/cli/tests/__init__.py create mode 100644 prereise/cli/tests/test_data_sources.py create mode 100644 prereise/cli/tests/test_helpers.py diff --git a/README.md b/README.md index 3d63d1404..9f201504b 100644 --- a/README.md +++ b/README.md @@ -75,6 +75,33 @@ differentiated using a lowercase letter added right after the year, e.g, ### A. Wind data +#### How to download + +Wind data can be downloaded via a python script. When in the terminal at the project +root directory, you can run: + +```bash +python -m prereise.cli.download.download_manager wind_data \ + --region REGION \ + --start_date START_DATE \ + --end_date END_DATE \ + --file_path FILEPATH +``` + +For example, if you would like to download the wind data for regions Texas and Western +between the dates of June 5th, 2020 and Janurary 2nd, 2021 into data.pkl, you can run: + +```bash +python -m prereise.cli.download.download_manager wind_data \ + --region Texas \ + --region Western \ + --start_date 2020-05-06 \ + --end_date 2021-01-02 \ + --file_path ./data.pkl +``` +You can run `python -m prereise.cli.download.download_manager wind_data -h` for more +details. + #### i. Rapid Refresh [RAP][RAP] (Rapid Refresh) is the continental-scale NOAA hourly-updated assimilation/modeling system operational at the National Centers for Environmental diff --git a/prereise/cli/__init__.py b/prereise/cli/__init__.py new file mode 100644 index 000000000..e69de29bb diff --git a/prereise/cli/constants.py b/prereise/cli/constants.py new file mode 100644 index 000000000..841f4e38e --- /dev/null +++ b/prereise/cli/constants.py @@ -0,0 +1 @@ +DATE_FMT = "%Y-%m-%d" diff --git a/prereise/cli/data_sources.py b/prereise/cli/data_sources.py new file mode 100644 index 000000000..801d29fca --- /dev/null +++ b/prereise/cli/data_sources.py @@ -0,0 +1,138 @@ +import logging +from abc import ABCMeta, abstractmethod +from datetime import datetime + +from powersimdata.input.grid import Grid + +from prereise.cli.constants import DATE_FMT +from prereise.cli.helpers import validate_date, validate_file_path +from prereise.gather.winddata.rap import rap + + +class DataSource(metaclass=ABCMeta): + """Abstract class that defines a strict interface + that future data sources need to follow in order + to seamlessly integrate with the parser. + + :param abc.ABCMeta metaclass: defaults to ABCMeta + """ + + @property + @abstractmethod + def command_name(self): + """String command name for argparse. See add_parser function + at `this link `_. + """ + pass + + @property + @abstractmethod + def command_help(self): + """String with a help description for the command. See add_parser function + at `this link `_ + for more details + """ + pass + + @property + @abstractmethod + def extract_arguments(self): + """List of dictionaries defining the various flags and parameters + the user needs to pass into this command, which are + subsequently passed to the below extract function. + See `add_argument `_ + to understand what is acceptable/unacceptable in these + dictionaries. + """ + pass + + @abstractmethod + def extract(self): + """Function that takes in the arguments defined in + the above property extract_arguments and downloads + the appropriate data and saves it somewhere. + """ + pass + + +class WindData(DataSource): + @property + def command_name(self): + """See :py:func:`prereise.cli.data_sources.DataSource.command_name` + + :return: (*str*) + """ + return "wind_data" + + @property + def command_help(self): + """See :py:func:`prereise.cli.data_sources.DataSource.command_help` + + :return: (*str*) + """ + return "Download wind data" + + @property + def extract_arguments(self): + """See :py:func:`prereise.cli.data_sources.DataSource.extract_arguments` + + :return: (*str*) + """ + return [ + { + "command_flags": ["--region", "-r"], + "required": True, + "choices": ["Texas", "Eastern", "Western"], + "type": str, + "action": "append", + }, + { + "command_flags": ["--start_date", "-sd"], + "required": True, + "type": validate_date, + "help": "The start date for the data download in format 'YYYY-MM-DD'", + }, + { + "command_flags": ["--end_date", "-ed"], + "required": True, + "type": validate_date, + "help": "The end date for the data download in format 'YYYY-MM-DD'", + }, + { + "command_flags": ["--file_path", "-fp"], + "required": True, + "type": validate_file_path, + "help": "The file path to store the downloaded data. Must include filename " + "and .pkl file extension.", + }, + ] + + def extract(self, region, start_date, end_date, file_path, **kwargs): + """See :py:func:`prereise.cli.data_sources.DataSource.extract` + + :param list region: list of regions to download wind farm data for + :param str start_date: date designating when to start the data download + :param str end_date: date designating when to end the data download + :param str file_path: file location on local filesystem on where to store the data + """ + regions = list(set(region)) + assert datetime.strptime(start_date, DATE_FMT) <= datetime.strptime( + end_date, DATE_FMT + ) + + grid = Grid(regions) + wind_farms = grid.plant.groupby("type").get_group("wind") + data, missing = rap.retrieve_data( + wind_farms, start_date=start_date, end_date=end_date + ) + if len(missing) > 0: + logging.warning(f"There are {len(missing)} files missing") + data.to_pickle(file_path) + + +def get_data_sources_list(): + """Provides list of all data sources + + :return: (*list*) + """ + return [WindData()] diff --git a/prereise/cli/download/__init__.py b/prereise/cli/download/__init__.py new file mode 100644 index 000000000..e69de29bb diff --git a/prereise/cli/download/download_manager.py b/prereise/cli/download/download_manager.py new file mode 100644 index 000000000..22cf7ca85 --- /dev/null +++ b/prereise/cli/download/download_manager.py @@ -0,0 +1,28 @@ +import argparse + +from prereise.cli.data_sources import get_data_sources_list +from prereise.cli.helpers import add_data_source_to_download_parser + + +def generate_parser(): + """Creates main command line interface parser + + :return: (*argparse.ArgumentParser*) + """ + parser = argparse.ArgumentParser() + for data_source in get_data_sources_list(): + add_data_source_to_download_parser(data_source, parser) + return parser + + +def main(): + """Main function that initializes parser and calls parser + with arguments the user passed in via command line interface + """ + parser = generate_parser() + args = parser.parse_args() + args.func(**args.__dict__) + + +if __name__ == "__main__": + main() diff --git a/prereise/cli/download/tests/__init__.py b/prereise/cli/download/tests/__init__.py new file mode 100644 index 000000000..e69de29bb diff --git a/prereise/cli/download/tests/test_download_manager.py b/prereise/cli/download/tests/test_download_manager.py new file mode 100644 index 000000000..c0bfeb443 --- /dev/null +++ b/prereise/cli/download/tests/test_download_manager.py @@ -0,0 +1,48 @@ +import pytest + +from prereise.cli.download.download_manager import generate_parser + +START_DATE = "2020-01-01" +END_DATE = "2021-01-01" +FILE_PATH = "./data.pkl" +REGION = "Texas" + +WIND_DATA_ARG_LIST_FULL_FLAGS = [ + "wind_data", + f"--start_date={START_DATE}", + f"--end_date={END_DATE}", + f"--file_path={FILE_PATH}", + f"--region={REGION}", +] + +WIND_DATA_ARG_LIST_SHORT_FLAGS = [ + "wind_data", + f"-sd={START_DATE}", + f"-ed={END_DATE}", + f"-fp={FILE_PATH}", + f"-r={REGION}", +] + + +@pytest.mark.parametrize( + "args", [WIND_DATA_ARG_LIST_FULL_FLAGS, WIND_DATA_ARG_LIST_SHORT_FLAGS] +) +def test_parser_wind_data(args): + parser = generate_parser() + result = parser.parse_args(args) + assert START_DATE == result.start_date + assert END_DATE == result.end_date + assert REGION in result.region + assert FILE_PATH == result.file_path + + +@pytest.mark.parametrize( + "args", [WIND_DATA_ARG_LIST_FULL_FLAGS, WIND_DATA_ARG_LIST_SHORT_FLAGS] +) +def test_parser_wind_data_missing_flags(args): + parser = generate_parser() + for arg in args: + bad_arg_list = args.copy() + bad_arg_list.remove(arg) + with pytest.raises(SystemExit): + parser.parse_args(bad_arg_list) diff --git a/prereise/cli/helpers.py b/prereise/cli/helpers.py new file mode 100644 index 000000000..15518c96f --- /dev/null +++ b/prereise/cli/helpers.py @@ -0,0 +1,52 @@ +import logging +import os +from datetime import datetime + +from prereise.cli.constants import DATE_FMT + + +def validate_date(date_string): + """Helper function to validate date strings + + :param str date_string: date in string format to be validated + :return: (*str*) -- validated date string + """ + datetime.strptime(date_string, DATE_FMT) + return date_string + + +def validate_file_path(file_path): + """Helper function to validate file paths + + :param str file_path: path include filename for where + to save the file + :raises ValueError: if the provided file path is not accessible + :return: (*str*) -- validated file path + """ + if not os.access(os.path.dirname(file_path), os.W_OK): + raise ValueError("Please choose a valid file path") + if os.path.isdir(file_path): + raise ValueError("Please provide a filename with a .pkl extension") + if os.path.isfile(file_path): + logging.warning("File exists! Will overwrite file at end of download!") + return file_path + + +def add_data_source_to_download_parser(data_source, parser): + """Helper function that adds an additional source of data + that the user can interact with and download via the + command line tool + + :param prereise.cli.data_sources.DataSource data_source: an + instance of a class that implements the abstract class DataSource + :param argparse.ArgumentParser parser: parser that implements command + line interface functionality + """ + subparsers = parser.add_subparsers() + subparser = subparsers.add_parser( + data_source.command_name, help=data_source.command_help + ) + for argument in data_source.extract_arguments: + command = argument.pop("command_flags") + subparser.add_argument(*command, **argument) + subparser.set_defaults(func=data_source.extract) diff --git a/prereise/cli/tests/__init__.py b/prereise/cli/tests/__init__.py new file mode 100644 index 000000000..e69de29bb diff --git a/prereise/cli/tests/test_data_sources.py b/prereise/cli/tests/test_data_sources.py new file mode 100644 index 000000000..1ba108bee --- /dev/null +++ b/prereise/cli/tests/test_data_sources.py @@ -0,0 +1,87 @@ +from unittest.mock import MagicMock, patch + +import pytest + +from prereise.cli.data_sources import WindData, get_data_sources_list + +TEXAS_REGION_LIST = ["Texas"] +STRING_DATE_2021_12_1 = "2021-12-1" +STRING_DATE_2021_5_1 = "2019-5-1" +CURRENT_DIRECTORY_FILEPATH = "./" + + +@pytest.fixture +def wind_data_object(): + return WindData() + + +def test_winddata_end_date_before_start_date(wind_data_object): + with pytest.raises(AssertionError): + wind_data_object.extract( + TEXAS_REGION_LIST, + STRING_DATE_2021_12_1, + STRING_DATE_2021_5_1, + CURRENT_DIRECTORY_FILEPATH, + ) + + +@patch("prereise.cli.data_sources.rap") +@patch("prereise.cli.data_sources.Grid") +def test_winddata_happy_path(grid, rap, wind_data_object): + grid_mock = MagicMock() + wind_farms = MagicMock() + grid_mock.plant.groupby.return_value.get_group.return_value = wind_farms + data = MagicMock() + rap.retrieve_data.return_value = (data, []) + grid.return_value = grid_mock + wind_data_object.extract( + TEXAS_REGION_LIST, + STRING_DATE_2021_5_1, + STRING_DATE_2021_12_1, + CURRENT_DIRECTORY_FILEPATH, + ) + rap.retrieve_data.assert_called_with( + wind_farms, start_date=STRING_DATE_2021_5_1, end_date=STRING_DATE_2021_12_1 + ) + data.to_pickle.assert_called_with(CURRENT_DIRECTORY_FILEPATH) + + +@patch("prereise.cli.data_sources.rap") +@patch("prereise.cli.data_sources.Grid") +@patch("prereise.cli.data_sources.logging") +def test_winddata_missing_files(logging, grid, rap, wind_data_object): + grid_mock = MagicMock() + wind_farms = MagicMock() + grid_mock.plant.groupby.return_value.get_group.return_value = wind_farms + data = MagicMock() + rap.retrieve_data.return_value = (data, [None, None]) + grid.return_value = grid_mock + wind_data_object.extract( + TEXAS_REGION_LIST, + STRING_DATE_2021_5_1, + STRING_DATE_2021_12_1, + CURRENT_DIRECTORY_FILEPATH, + ) + rap.retrieve_data.assert_called_with( + wind_farms, start_date=STRING_DATE_2021_5_1, end_date=STRING_DATE_2021_12_1 + ) + data.to_pickle.assert_called_with(CURRENT_DIRECTORY_FILEPATH) + logging.warning.assert_called_with("There are 2 files missing") + + +@patch("prereise.cli.data_sources.rap") +@patch("prereise.cli.data_sources.Grid") +def test_winddata_repeated_regions(grid, rap, wind_data_object): + rap.retrieve_data.return_value = (MagicMock(), [None, None]) + wind_data_object.extract( + [TEXAS_REGION_LIST[0], TEXAS_REGION_LIST[0]], + STRING_DATE_2021_5_1, + STRING_DATE_2021_12_1, + CURRENT_DIRECTORY_FILEPATH, + ) + grid.assert_called_with(TEXAS_REGION_LIST) + + +def test_get_data_sources_list(): + data_sources_list = get_data_sources_list() + assert isinstance(data_sources_list[0], WindData) diff --git a/prereise/cli/tests/test_helpers.py b/prereise/cli/tests/test_helpers.py new file mode 100644 index 000000000..a5591a136 --- /dev/null +++ b/prereise/cli/tests/test_helpers.py @@ -0,0 +1,69 @@ +from unittest.mock import MagicMock, patch + +import pytest + +from prereise.cli.helpers import ( + add_data_source_to_download_parser, + validate_date, + validate_file_path, +) + + +@pytest.fixture +def data_source(): + data_source_mock = MagicMock() + data_source_mock.command_name = "command_name" + data_source_mock.command_help = "command_help" + data_source_mock.extract_arguments = [ + {"command_flags": ["--command"], "keyarg": "value"} + ] + data_source_mock.extract = MagicMock() + return data_source_mock + + +def test_validate_date(): + date = "2020-01-03" + assert validate_date(date) == date + + +def test_validate_date_bad_date(): + with pytest.raises(ValueError): + validate_date("2020-01-49") + + +@patch("prereise.cli.helpers.os") +def test_validate_file_path(os): + file_path = "somefilepath" + os.access.return_value = True + os.path.isdir.return_value = False + assert validate_file_path(file_path) == file_path + + +@patch("prereise.cli.helpers.os") +def test_validate_file_path_bad_path(os): + os.access.return_value = False + with pytest.raises(ValueError) as e: + validate_file_path("somefilepath") + assert "Please choose a valid file path" in str(e.value) + + +@patch("prereise.cli.helpers.os") +def test_validate_file_path_is_direcotry(os): + os.access.return_value = True + os.path.isdir.return_value = True + with pytest.raises(ValueError) as e: + validate_file_path("/") + assert "Please provide a filename with a .pkl extension" in str(e.value) + + +def test_add_data_source_to_download_parser(data_source): + parser = MagicMock() + subparsers = MagicMock() + subparser = MagicMock() + subparsers.add_parser.return_value = subparser + parser.add_subparsers.return_value = subparsers + add_data_source_to_download_parser(data_source, parser) + subparsers.add_parser.assert_called_with( + data_source.command_name, help=data_source.command_help + ) + subparser.add_argument.assert_called_with("--command", keyarg="value") From 8975494d891e2d6eaab20fe83a280d0a2c458e8b Mon Sep 17 00:00:00 2001 From: George Tong Date: Wed, 23 Jun 2021 10:45:27 -0700 Subject: [PATCH 13/61] refactor: separate WindData and DataSource classes (#175) --- prereise/cli/data_sources/__init__.py | 9 +++ prereise/cli/data_sources/data_source.py | 47 ++++++++++++++ prereise/cli/data_sources/tests/__init__.py | 0 .../data_sources/tests/test_data_source.py | 7 ++ .../tests/test_wind_data.py} | 21 +++--- .../wind_data.py} | 64 ++----------------- prereise/cli/helpers.py | 2 +- 7 files changed, 77 insertions(+), 73 deletions(-) create mode 100644 prereise/cli/data_sources/__init__.py create mode 100644 prereise/cli/data_sources/data_source.py create mode 100644 prereise/cli/data_sources/tests/__init__.py create mode 100644 prereise/cli/data_sources/tests/test_data_source.py rename prereise/cli/{tests/test_data_sources.py => data_sources/tests/test_wind_data.py} (82%) rename prereise/cli/{data_sources.py => data_sources/wind_data.py} (55%) diff --git a/prereise/cli/data_sources/__init__.py b/prereise/cli/data_sources/__init__.py new file mode 100644 index 000000000..d159d4c52 --- /dev/null +++ b/prereise/cli/data_sources/__init__.py @@ -0,0 +1,9 @@ +from prereise.cli.data_sources.wind_data import WindData + + +def get_data_sources_list(): + """Provides list of all data sources + + :return: (*list*) + """ + return [WindData()] diff --git a/prereise/cli/data_sources/data_source.py b/prereise/cli/data_sources/data_source.py new file mode 100644 index 000000000..0c2cd713a --- /dev/null +++ b/prereise/cli/data_sources/data_source.py @@ -0,0 +1,47 @@ +from abc import ABCMeta, abstractmethod + + +class DataSource(metaclass=ABCMeta): + """Abstract class that defines a strict interface + that future data sources need to follow in order + to seamlessly integrate with the parser. + + :param abc.ABCMeta metaclass: defaults to ABCMeta + """ + + @property + @abstractmethod + def command_name(self): + """String command name for argparse. See add_parser function + at `this link `_. + """ + pass + + @property + @abstractmethod + def command_help(self): + """String with a help description for the command. See add_parser function + at `this link `_ + for more details + """ + pass + + @property + @abstractmethod + def extract_arguments(self): + """List of dictionaries defining the various flags and parameters + the user needs to pass into this command, which are + subsequently passed to the below extract function. + See `add_argument `_ + to understand what is acceptable/unacceptable in these + dictionaries. + """ + pass + + @abstractmethod + def extract(self): + """Function that takes in the arguments defined in + the above property extract_arguments and downloads + the appropriate data and saves it somewhere. + """ + pass diff --git a/prereise/cli/data_sources/tests/__init__.py b/prereise/cli/data_sources/tests/__init__.py new file mode 100644 index 000000000..e69de29bb diff --git a/prereise/cli/data_sources/tests/test_data_source.py b/prereise/cli/data_sources/tests/test_data_source.py new file mode 100644 index 000000000..3a8bb6b8f --- /dev/null +++ b/prereise/cli/data_sources/tests/test_data_source.py @@ -0,0 +1,7 @@ +from prereise.cli.data_sources import get_data_sources_list +from prereise.cli.data_sources.wind_data import WindData + + +def test_get_data_sources_list(): + data_sources_list = get_data_sources_list() + assert isinstance(data_sources_list[0], WindData) diff --git a/prereise/cli/tests/test_data_sources.py b/prereise/cli/data_sources/tests/test_wind_data.py similarity index 82% rename from prereise/cli/tests/test_data_sources.py rename to prereise/cli/data_sources/tests/test_wind_data.py index 1ba108bee..c03b97680 100644 --- a/prereise/cli/tests/test_data_sources.py +++ b/prereise/cli/data_sources/tests/test_wind_data.py @@ -2,7 +2,7 @@ import pytest -from prereise.cli.data_sources import WindData, get_data_sources_list +from prereise.cli.data_sources.wind_data import WindData TEXAS_REGION_LIST = ["Texas"] STRING_DATE_2021_12_1 = "2021-12-1" @@ -25,8 +25,8 @@ def test_winddata_end_date_before_start_date(wind_data_object): ) -@patch("prereise.cli.data_sources.rap") -@patch("prereise.cli.data_sources.Grid") +@patch("prereise.cli.data_sources.wind_data.rap") +@patch("prereise.cli.data_sources.wind_data.Grid") def test_winddata_happy_path(grid, rap, wind_data_object): grid_mock = MagicMock() wind_farms = MagicMock() @@ -46,9 +46,9 @@ def test_winddata_happy_path(grid, rap, wind_data_object): data.to_pickle.assert_called_with(CURRENT_DIRECTORY_FILEPATH) -@patch("prereise.cli.data_sources.rap") -@patch("prereise.cli.data_sources.Grid") -@patch("prereise.cli.data_sources.logging") +@patch("prereise.cli.data_sources.wind_data.rap") +@patch("prereise.cli.data_sources.wind_data.Grid") +@patch("prereise.cli.data_sources.wind_data.logging") def test_winddata_missing_files(logging, grid, rap, wind_data_object): grid_mock = MagicMock() wind_farms = MagicMock() @@ -69,8 +69,8 @@ def test_winddata_missing_files(logging, grid, rap, wind_data_object): logging.warning.assert_called_with("There are 2 files missing") -@patch("prereise.cli.data_sources.rap") -@patch("prereise.cli.data_sources.Grid") +@patch("prereise.cli.data_sources.wind_data.rap") +@patch("prereise.cli.data_sources.wind_data.Grid") def test_winddata_repeated_regions(grid, rap, wind_data_object): rap.retrieve_data.return_value = (MagicMock(), [None, None]) wind_data_object.extract( @@ -80,8 +80,3 @@ def test_winddata_repeated_regions(grid, rap, wind_data_object): CURRENT_DIRECTORY_FILEPATH, ) grid.assert_called_with(TEXAS_REGION_LIST) - - -def test_get_data_sources_list(): - data_sources_list = get_data_sources_list() - assert isinstance(data_sources_list[0], WindData) diff --git a/prereise/cli/data_sources.py b/prereise/cli/data_sources/wind_data.py similarity index 55% rename from prereise/cli/data_sources.py rename to prereise/cli/data_sources/wind_data.py index 801d29fca..9a12cdff8 100644 --- a/prereise/cli/data_sources.py +++ b/prereise/cli/data_sources/wind_data.py @@ -1,64 +1,18 @@ import logging -from abc import ABCMeta, abstractmethod from datetime import datetime from powersimdata.input.grid import Grid from prereise.cli.constants import DATE_FMT +from prereise.cli.data_sources.data_source import DataSource from prereise.cli.helpers import validate_date, validate_file_path from prereise.gather.winddata.rap import rap -class DataSource(metaclass=ABCMeta): - """Abstract class that defines a strict interface - that future data sources need to follow in order - to seamlessly integrate with the parser. - - :param abc.ABCMeta metaclass: defaults to ABCMeta - """ - - @property - @abstractmethod - def command_name(self): - """String command name for argparse. See add_parser function - at `this link `_. - """ - pass - - @property - @abstractmethod - def command_help(self): - """String with a help description for the command. See add_parser function - at `this link `_ - for more details - """ - pass - - @property - @abstractmethod - def extract_arguments(self): - """List of dictionaries defining the various flags and parameters - the user needs to pass into this command, which are - subsequently passed to the below extract function. - See `add_argument `_ - to understand what is acceptable/unacceptable in these - dictionaries. - """ - pass - - @abstractmethod - def extract(self): - """Function that takes in the arguments defined in - the above property extract_arguments and downloads - the appropriate data and saves it somewhere. - """ - pass - - class WindData(DataSource): @property def command_name(self): - """See :py:func:`prereise.cli.data_sources.DataSource.command_name` + """See :py:func:`prereise.cli.data_sources.data_source.DataSource.command_name` :return: (*str*) """ @@ -66,7 +20,7 @@ def command_name(self): @property def command_help(self): - """See :py:func:`prereise.cli.data_sources.DataSource.command_help` + """See :py:func:`prereise.cli.data_sources.data_source.DataSource.command_help` :return: (*str*) """ @@ -74,7 +28,7 @@ def command_help(self): @property def extract_arguments(self): - """See :py:func:`prereise.cli.data_sources.DataSource.extract_arguments` + """See :py:func:`prereise.cli.data_sources.data_source.DataSource.extract_arguments` :return: (*str*) """ @@ -108,7 +62,7 @@ def extract_arguments(self): ] def extract(self, region, start_date, end_date, file_path, **kwargs): - """See :py:func:`prereise.cli.data_sources.DataSource.extract` + """See :py:func:`prereise.cli.data_sources.data_source.DataSource.extract` :param list region: list of regions to download wind farm data for :param str start_date: date designating when to start the data download @@ -128,11 +82,3 @@ def extract(self, region, start_date, end_date, file_path, **kwargs): if len(missing) > 0: logging.warning(f"There are {len(missing)} files missing") data.to_pickle(file_path) - - -def get_data_sources_list(): - """Provides list of all data sources - - :return: (*list*) - """ - return [WindData()] diff --git a/prereise/cli/helpers.py b/prereise/cli/helpers.py index 15518c96f..8bde8489c 100644 --- a/prereise/cli/helpers.py +++ b/prereise/cli/helpers.py @@ -37,7 +37,7 @@ def add_data_source_to_download_parser(data_source, parser): that the user can interact with and download via the command line tool - :param prereise.cli.data_sources.DataSource data_source: an + :param prereise.cli.data_sources.data_source.DataSource data_source: an instance of a class that implements the abstract class DataSource :param argparse.ArgumentParser parser: parser that implements command line interface functionality From c4c9b58cc4d7533587c10b081ff66dfb3660f37f Mon Sep 17 00:00:00 2001 From: jon-hagg <66005238+jon-hagg@users.noreply.github.com> Date: Fri, 25 Jun 2021 11:48:09 -0700 Subject: [PATCH 14/61] chore: update packages manually (#177) --- Pipfile | 2 +- Pipfile.lock | 252 +++++++++++++++++++++++++---------------------- requirements.txt | 2 +- 3 files changed, 135 insertions(+), 121 deletions(-) diff --git a/Pipfile b/Pipfile index 1bdb53f6a..4ded4426c 100644 --- a/Pipfile +++ b/Pipfile @@ -17,7 +17,7 @@ numpy = "~=1.19" pandas = "~=1.1.2" python-dateutil = "==2.7.5" requests = "~=2.24.0" -scipy = "==1.4.1" +scipy = "~=1.6" tqdm = "==4.29.1" xlrd = "==1.2.0" netCDF4 = "==1.5.4" diff --git a/Pipfile.lock b/Pipfile.lock index b4e907ad3..0fb7161d1 100644 --- a/Pipfile.lock +++ b/Pipfile.lock @@ -1,7 +1,7 @@ { "_meta": { "hash": { - "sha256": "99a0ccf964c137594bf784b32bc43083069964145135b9614874d8421964aba6" + "sha256": "b56ab9869068571dd50d58f3e38dafc75f289e9e531f0b10945f15154704dd38" }, "pipfile-spec": 6, "requires": {}, @@ -161,6 +161,13 @@ ], "version": "==0.10.0" }, + "decorator": { + "hashes": [ + "sha256:41fa54c2a0cc4ba648be4fd43cff00aedf5b9465c9bf18d64325bc225f08f760", + "sha256:e3a62f0520172440ca0dcc823749319382e377f37f140a0b99ef45fecb84bfe7" + ], + "version": "==4.4.2" + }, "h5pyd": { "hashes": [ "sha256:0ba9ee0afe8d5718c2984d490f73d5fb3fe1134d95bcfd68eee79ff99e6e6a9b", @@ -315,6 +322,14 @@ "index": "pypi", "version": "==1.5.4" }, + "networkx": { + "hashes": [ + "sha256:0635858ed7e989f4c574c2328380b452df892ae85084144c73d8cd819f0c4e06", + "sha256:109cd585cac41297f71103c3c42ac6ef7379f29788eb54cb751be5a663bb235a" + ], + "markers": "python_version >= '3.6'", + "version": "==2.5.1" + }, "nrel-pysam": { "hashes": [ "sha256:195572e5119bb3573ceb77507dc7238bca66de76d4152a0af79489d5f8cd0de6", @@ -341,35 +356,37 @@ }, "numpy": { "hashes": [ - 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**/test_*.py - **/__init__.py - diff --git a/.github/workflows/coverage.yml b/.github/workflows/coverage.yml new file mode 100644 index 000000000..98711d79b --- /dev/null +++ b/.github/workflows/coverage.yml @@ -0,0 +1,41 @@ +name: Code coverage + +on: + push: + branches: + - 'develop' + +jobs: + coverage: + runs-on: ubuntu-latest + + name: Generate coverage report + steps: + - name: Checkout PreREISE + uses: actions/checkout@v2 + with: + path: PreREISE + + - name: Checkout PowerSimData + uses: actions/checkout@v2 + with: + repository: Breakthrough-Energy/PowerSimData + path: PowerSimData + + - name: Set up Python + uses: actions/setup-python@v2 + with: + python-version: 3.8 + + - run: python -m pip install --upgrade pip tox + working-directory: PreREISE + + - run: tox -e pytest-local -- --cov-report=xml + working-directory: PreREISE + + - name: Upload coverage to Codecov + uses: codecov/codecov-action@v1 + with: + name: codecov-prereise + fail_ci_if_error: true + directory: PreREISE diff --git a/.github/workflows/packages.yml b/.github/workflows/packages.yml index 036ddf6d3..263d3ae8f 100644 --- a/.github/workflows/packages.yml +++ b/.github/workflows/packages.yml @@ -46,6 +46,7 @@ jobs: token: ${{ secrets.CI_TOKEN_CLONE_REPO }} commit-message: Update dependencies title: Update dependencies + labels: dependencies delete-branch: true body: | ### Summary of changes diff --git a/tox.ini b/tox.ini index 56d5b50cd..16a184e3c 100644 --- a/tox.ini +++ b/tox.ini @@ -14,7 +14,7 @@ deps = flake8: pep8-naming commands = pytest: pipenv sync --dev - local: pytest -m 'not integration' + local: pytest -m 'not integration' {posargs} integration: pytest format: black . format: isort . From 5e411abcc0a9ec61b25d85f72a676973b6befdcb Mon Sep 17 00:00:00 2001 From: Jon Hagg Date: Mon, 28 Jun 2021 14:55:48 -0700 Subject: [PATCH 16/61] chore: add badges --- README.md | 5 +++++ 1 file changed, 5 insertions(+) diff --git a/README.md b/README.md index 9f201504b..dc8c990d0 100644 --- a/README.md +++ b/README.md @@ -1,5 +1,10 @@ +![logo](https://raw.githubusercontent.com/Breakthrough-Energy/docs/master/source/_static/img/BE_Sciences_RGB_Horizontal_Color.svg) +[![codecov](https://codecov.io/gh/Breakthrough-Energy/PreREISE/branch/develop/graph/badge.svg?token=4KA0ESPUA4)](https://codecov.io/gh/Breakthrough-Energy/PreREISE) +[![made-with-python](https://img.shields.io/badge/Made%20with-Python-1f425f.svg)](https://www.python.org/) [![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black) ![Tests](https://github.com/Breakthrough-Energy/PreREISE/workflows/Pytest/badge.svg) +[![Documentation](https://github.com/Breakthrough-Energy/docs/actions/workflows/publish.yml/badge.svg)](https://breakthrough-energy.github.io/docs/) +[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT) # PreREISE This package gathers and builds demand, hydro, solar, and wind profiles. The profiles From 811922c0ebad7260f2ab2997d262b4166a8ce8ed Mon Sep 17 00:00:00 2001 From: jon-hagg <66005238+jon-hagg@users.noreply.github.com> Date: Wed, 7 Jul 2021 11:03:44 -0700 Subject: [PATCH 17/61] chore: fix N818 warning from pep8-naming (#183) --- prereise/gather/tests/test_retry.py | 16 ++++++++-------- 1 file changed, 8 insertions(+), 8 deletions(-) diff --git a/prereise/gather/tests/test_retry.py b/prereise/gather/tests/test_retry.py index 814a83b31..5d074be3b 100644 --- a/prereise/gather/tests/test_retry.py +++ b/prereise/gather/tests/test_retry.py @@ -3,15 +3,15 @@ from prereise.gather.request_util import retry -class CustomException(Exception): +class CustomError(Exception): pass def test_max_times_reached(): - @retry(max_attempts=3, allowed_exceptions=CustomException) + @retry(max_attempts=3, allowed_exceptions=CustomError) def no_fail(x=[]): x.append(len(x)) - raise CustomException() + raise CustomError() counts = [] no_fail(counts) @@ -19,11 +19,11 @@ def no_fail(x=[]): def test_raises_after_max_attempts(): - @retry(max_attempts=3, raises=True, allowed_exceptions=CustomException) + @retry(max_attempts=3, raises=True, allowed_exceptions=CustomError) def func(): - raise CustomException() + raise CustomError() - with pytest.raises(CustomException): + with pytest.raises(CustomError): func() @@ -55,11 +55,11 @@ def fail(): def test_counter_attribute(): limit = 3 - @retry(max_attempts=limit, allowed_exceptions=CustomException) + @retry(max_attempts=limit, allowed_exceptions=CustomError) def best_attempt(): x = best_attempt.retry_count if best_attempt.retry_count < limit: - raise CustomException + raise CustomError return x assert limit == best_attempt() From a0b7af215ca29e701c328cec992ddf87158ecdd6 Mon Sep 17 00:00:00 2001 From: George Tong Date: Wed, 7 Jul 2021 16:00:42 -0700 Subject: [PATCH 18/61] feat: add solar data cli downloader (#178) --- README.md | 63 +++++- prereise/cli/constants.py | 5 + prereise/cli/data_sources/__init__.py | 12 +- prereise/cli/data_sources/solar_data.py | 182 ++++++++++++++++++ prereise/cli/data_sources/tests/conftest.py | 8 + .../data_sources/tests/test_data_source.py | 10 +- .../cli/data_sources/tests/test_solar_data.py | 106 ++++++++++ .../cli/data_sources/tests/test_wind_data.py | 28 +-- prereise/cli/data_sources/wind_data.py | 26 +-- prereise/cli/download/download_manager.py | 3 +- .../download/tests/test_download_manager.py | 77 ++++++-- prereise/cli/helpers.py | 17 +- prereise/cli/tests/test_helpers.py | 15 +- 13 files changed, 482 insertions(+), 70 deletions(-) create mode 100644 prereise/cli/data_sources/solar_data.py create mode 100644 prereise/cli/data_sources/tests/conftest.py create mode 100644 prereise/cli/data_sources/tests/test_solar_data.py diff --git a/README.md b/README.md index dc8c990d0..cebc95fe8 100644 --- a/README.md +++ b/README.md @@ -78,34 +78,77 @@ differentiated using a lowercase letter added right after the year, e.g, ***demand_vJan2021c.csv*** (third) and so forth. -### A. Wind data +### How to download -#### How to download +Most data can be downloaded via our download manager python script. After setting +up the project via the [setup instructions](#1-setupinstall), when in the terminal +at the project root directory, you can run: -Wind data can be downloaded via a python script. When in the terminal at the project -root directory, you can run: +```bash +> python -m prereise.cli.download.download_manager -h +usage: download_manager.py [-h] + {wind_data_rap,solar_data_ga,solar_data_nsrdb} ... + +positional arguments: + {wind_data_rap,solar_data_ga,solar_data_nsrdb} + wind_data_rap Download wind data from National Centers for + Environmental Prediction + solar_data_ga Download solar data from the Gridded Atmospheric Wind + Integration National Dataset Toolkit + solar_data_nsrdb Download solar data from the National Solar Radiation + Database + +optional arguments: + -h, --help show this help message and exit +``` +Currently supported data sources to download from are: + +[Rapid Refresh from National Centers for Environmental Prediction](#i-rapid-refresh) ```bash -python -m prereise.cli.download.download_manager wind_data \ +python -m prereise.cli.download.download_manager wind_data_rap \ --region REGION \ --start_date START_DATE \ --end_date END_DATE \ --file_path FILEPATH ``` -For example, if you would like to download the wind data for regions Texas and Western -between the dates of June 5th, 2020 and Janurary 2nd, 2021 into data.pkl, you can run: +[Gridded Atmospheric Wind Integration National Dataset Toolkit](#i-the-gridded-atmospheric-wind-integration-national-dataset-toolkit) +```bash +python -m prereise.cli.download.download_manager solar_data_ga \ + --region REGION \ + --start_date START_DATE \ + --end_date END_DATE \ + --file_path FILEPATH \ + --key API_KEY +``` + +[The National Solar Radiation Database](#ii-the-national-solar-radiation-database) +```bash +python -m prereise.cli.download.download_manager solar_data_nsrdb \ + --region REGION \ + --method METHOD \ + --year YEAR \ + --file_path FILEPATH \ + --email EMAIL \ + --key API_KEY +``` +As a concrete example, if you would like to download the wind data from Rapid +Refresh from National Centers for Environmental Prediction for regions Texas and Western +between the dates of June 5th, 2020 and Janurary 2nd, 2021 into data.pkl, you can run: ```bash -python -m prereise.cli.download.download_manager wind_data \ +python -m prereise.cli.download.download_manager wind_data_rap \ --region Texas \ --region Western \ --start_date 2020-05-06 \ --end_date 2021-01-02 \ --file_path ./data.pkl ``` -You can run `python -m prereise.cli.download.download_manager wind_data -h` for more -details. +You can run `python -m prereise.cli.download.download_manager DATA_SOURCE_OPTION -h` for more +details, where `DATA_SOURCE_OPTION` is `wind_data_rap`, `solar_data_nsrdb`, etc. + +### A. Wind data #### i. Rapid Refresh [RAP][RAP] (Rapid Refresh) is the continental-scale NOAA hourly-updated diff --git a/prereise/cli/constants.py b/prereise/cli/constants.py index 841f4e38e..a6f566e4d 100644 --- a/prereise/cli/constants.py +++ b/prereise/cli/constants.py @@ -1 +1,6 @@ DATE_FMT = "%Y-%m-%d" +YEAR_FMT = "%Y" +START_DATE_HELP_STRING = "The start date for the data download in format 'YYYY-MM-DD'" +END_DATE_HELP_STRING = "The end date for the data download in format 'YYYY-MM-DD'" +FILE_PATH_HELP_STRING = "The file path to store the downloaded data. Must include filename and .pkl file extension." +REGION_CHOICES = ["Texas", "Eastern", "Western"] diff --git a/prereise/cli/data_sources/__init__.py b/prereise/cli/data_sources/__init__.py index d159d4c52..3928779b3 100644 --- a/prereise/cli/data_sources/__init__.py +++ b/prereise/cli/data_sources/__init__.py @@ -1,4 +1,8 @@ -from prereise.cli.data_sources.wind_data import WindData +from prereise.cli.data_sources.solar_data import ( + SolarDataGriddedAtmospheric, + SolarDataNationalSolarRadiationDatabase, +) +from prereise.cli.data_sources.wind_data import WindDataRapidRefresh def get_data_sources_list(): @@ -6,4 +10,8 @@ def get_data_sources_list(): :return: (*list*) """ - return [WindData()] + return [ + WindDataRapidRefresh(), + SolarDataGriddedAtmospheric(), + SolarDataNationalSolarRadiationDatabase(), + ] diff --git a/prereise/cli/data_sources/solar_data.py b/prereise/cli/data_sources/solar_data.py new file mode 100644 index 000000000..c65541f32 --- /dev/null +++ b/prereise/cli/data_sources/solar_data.py @@ -0,0 +1,182 @@ +from datetime import datetime + +from powersimdata.input.grid import Grid + +from prereise.cli.constants import ( + DATE_FMT, + END_DATE_HELP_STRING, + FILE_PATH_HELP_STRING, + REGION_CHOICES, + START_DATE_HELP_STRING, +) +from prereise.cli.data_sources.data_source import DataSource +from prereise.cli.helpers import validate_date, validate_file_path, validate_year +from prereise.gather.solardata.ga_wind import ga_wind +from prereise.gather.solardata.nsrdb import naive, sam + +API_KEY_HELP_STRING = ( + "API key that can be requested at https://developer.nrel.gov/signup/" +) +NAIVE_STRING = "naive" +SAM_STRING = "sam" + + +class SolarDataGriddedAtmospheric(DataSource): + @property + def command_name(self): + """See :py:func:`prereise.cli.data_sources.data_source.DataSource.command_name` + + :return: (*str*) + """ + return "solar_data_ga" + + @property + def command_help(self): + """See :py:func:`prereise.cli.data_sources.data_source.DataSource.command_help` + + :return: (*str*) + """ + return "Download solar data from the Gridded Atmospheric Wind Integration National Dataset Toolkit" + + @property + def extract_arguments(self): + """See :py:func:`prereise.cli.data_sources.data_source.DataSource.extract_arguments` + + :return: (*str*) + """ + return [ + { + "command_flags": ["--region", "-r"], + "required": True, + "choices": REGION_CHOICES, + "type": str, + "action": "append", + }, + { + "command_flags": ["--start_date", "-sd"], + "required": True, + "type": validate_date, + "help": START_DATE_HELP_STRING, + }, + { + "command_flags": ["--end_date", "-ed"], + "required": True, + "type": validate_date, + "help": END_DATE_HELP_STRING, + }, + { + "command_flags": ["--file_path", "-fp"], + "required": True, + "type": validate_file_path, + "help": FILE_PATH_HELP_STRING, + }, + { + "command_flags": ["--key", "-k"], + "required": True, + "type": str, + "help": API_KEY_HELP_STRING, + }, + ] + + def extract(self, region, start_date, end_date, file_path, key, **kwargs): + """See :py:func:`prereise.cli.data_sources.data_source.DataSource.extract` + + :param list region: list of regions to download data for + :param str start_date: date designating when to start the data download + :param str end_date: date designating when to end the data download + :param str file_path: file location on local filesystem on where to store the data + :param str key: API key that can be requested at https://developer.nrel.gov/signup/ + """ + assert datetime.strptime(start_date, DATE_FMT) <= datetime.strptime( + end_date, DATE_FMT + ) + grid = Grid(region) + solar_plants = grid.plant.groupby("type").get_group("solar") + data = ga_wind.retrieve_data( + solar_plants, key, start_date=start_date, end_date=end_date + ) + data.to_pickle(file_path) + + +class SolarDataNationalSolarRadiationDatabase(DataSource): + @property + def command_name(self): + """See :py:func:`prereise.cli.data_sources.data_source.DataSource.command_name` + + :return: (*str*) + """ + return "solar_data_nsrdb" + + @property + def command_help(self): + """See :py:func:`prereise.cli.data_sources.data_source.DataSource.command_help` + + :return: (*str*) + """ + return "Download solar data from the National Solar Radiation Database" + + @property + def extract_arguments(self): + """See :py:func:`prereise.cli.data_sources.data_source.DataSource.extract_arguments` + + :return: (*str*) + """ + return [ + { + "command_flags": ["--region", "-r"], + "required": True, + "choices": REGION_CHOICES, + "type": str, + "action": "append", + }, + { + "command_flags": ["--method", "-m"], + "required": True, + "choices": [NAIVE_STRING, SAM_STRING], + "type": str, + }, + { + "command_flags": ["--year", "-y"], + "required": True, + "type": validate_year, + "help": "The start date for the data download in format 'YYYY'", + }, + { + "command_flags": ["--file_path", "-fp"], + "required": True, + "type": validate_file_path, + "help": FILE_PATH_HELP_STRING, + }, + { + "command_flags": ["--email", "-e"], + "required": True, + "type": str, + "help": "Email used to sign up at https://developer.nrel.gov/signup/", + }, + { + "command_flags": ["--key", "-k"], + "required": True, + "type": str, + "help": API_KEY_HELP_STRING, + }, + ] + + def extract(self, region, method, year, file_path, email, key, **kwargs): + """See :py:func:`prereise.cli.data_sources.data_source.DataSource.extract` + + :param list region: list of regions to download data for + :param str method: string indicating the modeling for power output + :param str year: string in the format YYYY denoting year to download from + :param str file_path: file location on local filesystem on where to store the data + :param str email: email used to sign up at https://developer.nrel.gov/signup/ + :param str key: API key that can be requested at https://developer.nrel.gov/signup/ + """ + grid = Grid(region) + solar_plants = grid.plant.groupby("type").get_group("solar") + if method == NAIVE_STRING: + data = naive.retrieve_data(solar_plants, email, key, year) + elif method == SAM_STRING: + data = sam.retrieve_data(solar_plants, email, key, year) + else: + raise ValueError(f"Unexpected method {method}") + data.to_pickle(file_path) diff --git a/prereise/cli/data_sources/tests/conftest.py b/prereise/cli/data_sources/tests/conftest.py new file mode 100644 index 000000000..c85dfd9ce --- /dev/null +++ b/prereise/cli/data_sources/tests/conftest.py @@ -0,0 +1,8 @@ +TEXAS_REGION_LIST = ["Texas"] +STRING_DATE_2021_12_1 = "2021-12-1" +STRING_DATE_2021_5_1 = "2021-5-1" +CURRENT_DIRECTORY_FILEPATH = "./somefile.pkl" +EMAIL = "fakeemail@bev.com" +API_KEY = "FAKE_API_KEY" +STRING_YEAR_2020 = "2020" +INVALID_METHOD = "gibberish" diff --git a/prereise/cli/data_sources/tests/test_data_source.py b/prereise/cli/data_sources/tests/test_data_source.py index 3a8bb6b8f..2a2104970 100644 --- a/prereise/cli/data_sources/tests/test_data_source.py +++ b/prereise/cli/data_sources/tests/test_data_source.py @@ -1,7 +1,13 @@ from prereise.cli.data_sources import get_data_sources_list -from prereise.cli.data_sources.wind_data import WindData +from prereise.cli.data_sources.solar_data import ( + SolarDataGriddedAtmospheric, + SolarDataNationalSolarRadiationDatabase, +) +from prereise.cli.data_sources.wind_data import WindDataRapidRefresh def test_get_data_sources_list(): data_sources_list = get_data_sources_list() - assert isinstance(data_sources_list[0], WindData) + assert isinstance(data_sources_list[0], WindDataRapidRefresh) + assert isinstance(data_sources_list[1], SolarDataGriddedAtmospheric) + assert isinstance(data_sources_list[2], SolarDataNationalSolarRadiationDatabase) diff --git a/prereise/cli/data_sources/tests/test_solar_data.py b/prereise/cli/data_sources/tests/test_solar_data.py new file mode 100644 index 000000000..d0e47bbdd --- /dev/null +++ b/prereise/cli/data_sources/tests/test_solar_data.py @@ -0,0 +1,106 @@ +from unittest.mock import MagicMock, patch + +import pytest + +from prereise.cli.data_sources.solar_data import ( + NAIVE_STRING, + SAM_STRING, + SolarDataGriddedAtmospheric, + SolarDataNationalSolarRadiationDatabase, +) +from prereise.cli.data_sources.tests.conftest import ( + API_KEY, + CURRENT_DIRECTORY_FILEPATH, + EMAIL, + INVALID_METHOD, + STRING_DATE_2021_5_1, + STRING_DATE_2021_12_1, + STRING_YEAR_2020, + TEXAS_REGION_LIST, +) + + +@pytest.fixture +def solar_data_ga_object(): + return SolarDataGriddedAtmospheric() + + +@pytest.fixture +def solar_data_nsrdb_object(): + return SolarDataNationalSolarRadiationDatabase() + + +def test_solar_data_ga_end_date_before_start_date(solar_data_ga_object): + with pytest.raises(AssertionError): + solar_data_ga_object.extract( + TEXAS_REGION_LIST, + STRING_DATE_2021_12_1, + STRING_DATE_2021_5_1, + CURRENT_DIRECTORY_FILEPATH, + API_KEY, + ) + + +@patch("prereise.cli.data_sources.solar_data.ga_wind") +@patch("prereise.cli.data_sources.solar_data.Grid") +def test_solar_data_ga_happy_path(grid, ga_wind, solar_data_ga_object): + solar_farms = MagicMock() + data = MagicMock() + ga_wind.retrieve_data.return_value = data + grid.return_value.plant.groupby.return_value.get_group.return_value = solar_farms + solar_data_ga_object.extract( + TEXAS_REGION_LIST, + STRING_DATE_2021_5_1, + STRING_DATE_2021_12_1, + CURRENT_DIRECTORY_FILEPATH, + API_KEY, + ) + ga_wind.retrieve_data.assert_called_with( + solar_farms, + API_KEY, + start_date=STRING_DATE_2021_5_1, + end_date=STRING_DATE_2021_12_1, + ) + data.to_pickle.assert_called_with(CURRENT_DIRECTORY_FILEPATH) + + +def test_solar_data_nsrdb_invalid_method(solar_data_nsrdb_object): + with pytest.raises(ValueError): + solar_data_nsrdb_object.extract( + TEXAS_REGION_LIST, + INVALID_METHOD, + STRING_YEAR_2020, + CURRENT_DIRECTORY_FILEPATH, + EMAIL, + API_KEY, + ) + + +@patch("prereise.cli.data_sources.solar_data.Grid") +def test_solar_data_nsrdb_happy_path(grid, solar_data_nsrdb_object): + + methods_to_test = [ + ("prereise.cli.data_sources.solar_data.sam", SAM_STRING), + ("prereise.cli.data_sources.solar_data.naive", NAIVE_STRING), + ] + + for patch_path, method_string in methods_to_test: + with patch(patch_path) as method: + solar_farms = MagicMock() + data = MagicMock() + method.retrieve_data.return_value = data + grid.return_value.plant.groupby.return_value.get_group.return_value = ( + solar_farms + ) + solar_data_nsrdb_object.extract( + TEXAS_REGION_LIST, + method_string, + STRING_YEAR_2020, + CURRENT_DIRECTORY_FILEPATH, + EMAIL, + API_KEY, + ) + method.retrieve_data.assert_called_with( + solar_farms, EMAIL, API_KEY, STRING_YEAR_2020 + ) + data.to_pickle.assert_called_with(CURRENT_DIRECTORY_FILEPATH) diff --git a/prereise/cli/data_sources/tests/test_wind_data.py b/prereise/cli/data_sources/tests/test_wind_data.py index c03b97680..56eafecd1 100644 --- a/prereise/cli/data_sources/tests/test_wind_data.py +++ b/prereise/cli/data_sources/tests/test_wind_data.py @@ -2,17 +2,18 @@ import pytest -from prereise.cli.data_sources.wind_data import WindData - -TEXAS_REGION_LIST = ["Texas"] -STRING_DATE_2021_12_1 = "2021-12-1" -STRING_DATE_2021_5_1 = "2019-5-1" -CURRENT_DIRECTORY_FILEPATH = "./" +from prereise.cli.data_sources.tests.conftest import ( + CURRENT_DIRECTORY_FILEPATH, + STRING_DATE_2021_5_1, + STRING_DATE_2021_12_1, + TEXAS_REGION_LIST, +) +from prereise.cli.data_sources.wind_data import WindDataRapidRefresh @pytest.fixture def wind_data_object(): - return WindData() + return WindDataRapidRefresh() def test_winddata_end_date_before_start_date(wind_data_object): @@ -67,16 +68,3 @@ def test_winddata_missing_files(logging, grid, rap, wind_data_object): ) data.to_pickle.assert_called_with(CURRENT_DIRECTORY_FILEPATH) logging.warning.assert_called_with("There are 2 files missing") - - -@patch("prereise.cli.data_sources.wind_data.rap") -@patch("prereise.cli.data_sources.wind_data.Grid") -def test_winddata_repeated_regions(grid, rap, wind_data_object): - rap.retrieve_data.return_value = (MagicMock(), [None, None]) - wind_data_object.extract( - [TEXAS_REGION_LIST[0], TEXAS_REGION_LIST[0]], - STRING_DATE_2021_5_1, - STRING_DATE_2021_12_1, - CURRENT_DIRECTORY_FILEPATH, - ) - grid.assert_called_with(TEXAS_REGION_LIST) diff --git a/prereise/cli/data_sources/wind_data.py b/prereise/cli/data_sources/wind_data.py index 9a12cdff8..a124ebe6c 100644 --- a/prereise/cli/data_sources/wind_data.py +++ b/prereise/cli/data_sources/wind_data.py @@ -3,20 +3,26 @@ from powersimdata.input.grid import Grid -from prereise.cli.constants import DATE_FMT +from prereise.cli.constants import ( + DATE_FMT, + END_DATE_HELP_STRING, + FILE_PATH_HELP_STRING, + REGION_CHOICES, + START_DATE_HELP_STRING, +) from prereise.cli.data_sources.data_source import DataSource from prereise.cli.helpers import validate_date, validate_file_path from prereise.gather.winddata.rap import rap -class WindData(DataSource): +class WindDataRapidRefresh(DataSource): @property def command_name(self): """See :py:func:`prereise.cli.data_sources.data_source.DataSource.command_name` :return: (*str*) """ - return "wind_data" + return "wind_data_rap" @property def command_help(self): @@ -24,7 +30,7 @@ def command_help(self): :return: (*str*) """ - return "Download wind data" + return "Download wind data from National Centers for Environmental Prediction" @property def extract_arguments(self): @@ -36,7 +42,7 @@ def extract_arguments(self): { "command_flags": ["--region", "-r"], "required": True, - "choices": ["Texas", "Eastern", "Western"], + "choices": REGION_CHOICES, "type": str, "action": "append", }, @@ -44,20 +50,19 @@ def extract_arguments(self): "command_flags": ["--start_date", "-sd"], "required": True, "type": validate_date, - "help": "The start date for the data download in format 'YYYY-MM-DD'", + "help": START_DATE_HELP_STRING, }, { "command_flags": ["--end_date", "-ed"], "required": True, "type": validate_date, - "help": "The end date for the data download in format 'YYYY-MM-DD'", + "help": END_DATE_HELP_STRING, }, { "command_flags": ["--file_path", "-fp"], "required": True, "type": validate_file_path, - "help": "The file path to store the downloaded data. Must include filename " - "and .pkl file extension.", + "help": FILE_PATH_HELP_STRING, }, ] @@ -69,12 +74,11 @@ def extract(self, region, start_date, end_date, file_path, **kwargs): :param str end_date: date designating when to end the data download :param str file_path: file location on local filesystem on where to store the data """ - regions = list(set(region)) assert datetime.strptime(start_date, DATE_FMT) <= datetime.strptime( end_date, DATE_FMT ) - grid = Grid(regions) + grid = Grid(region) wind_farms = grid.plant.groupby("type").get_group("wind") data, missing = rap.retrieve_data( wind_farms, start_date=start_date, end_date=end_date diff --git a/prereise/cli/download/download_manager.py b/prereise/cli/download/download_manager.py index 22cf7ca85..d7f1f4d38 100644 --- a/prereise/cli/download/download_manager.py +++ b/prereise/cli/download/download_manager.py @@ -10,8 +10,9 @@ def generate_parser(): :return: (*argparse.ArgumentParser*) """ parser = argparse.ArgumentParser() + subparser = parser.add_subparsers() for data_source in get_data_sources_list(): - add_data_source_to_download_parser(data_source, parser) + add_data_source_to_download_parser(data_source, subparser) return parser diff --git a/prereise/cli/download/tests/test_download_manager.py b/prereise/cli/download/tests/test_download_manager.py index c0bfeb443..d79aba016 100644 --- a/prereise/cli/download/tests/test_download_manager.py +++ b/prereise/cli/download/tests/test_download_manager.py @@ -6,40 +6,83 @@ END_DATE = "2021-01-01" FILE_PATH = "./data.pkl" REGION = "Texas" +EMAIL = "fakeemail@bev.com" +API_KEY = "FAKE_API_KEY" +STRING_YEAR_2020 = "2020" +METHOD = "sam" -WIND_DATA_ARG_LIST_FULL_FLAGS = [ - "wind_data", +WIND_DATA_RAP_ARG_LIST_FULL_FLAGS = [ + "wind_data_rap", f"--start_date={START_DATE}", f"--end_date={END_DATE}", f"--file_path={FILE_PATH}", f"--region={REGION}", ] -WIND_DATA_ARG_LIST_SHORT_FLAGS = [ - "wind_data", +WIND_DATA_RAP_ARG_LIST_SHORT_FLAGS = [ + "wind_data_rap", f"-sd={START_DATE}", f"-ed={END_DATE}", f"-fp={FILE_PATH}", f"-r={REGION}", ] +SOLAR_DATA_GA_ARG_LIST_FULL_FLAGS = [ + "solar_data_ga", + f"--start_date={START_DATE}", + f"--end_date={END_DATE}", + f"--file_path={FILE_PATH}", + f"--region={REGION}", + f"--key={API_KEY}", +] + +SOLAR_DATA_GA_ARG_LIST_SHORT_FLAGS = [ + "solar_data_ga", + f"-sd={START_DATE}", + f"-ed={END_DATE}", + f"-fp={FILE_PATH}", + f"-r={REGION}", + f"-k={API_KEY}", +] + +SOLAR_DATA_NSRDB_ARG_LIST_FULL_FLAGS = [ + "solar_data_nsrdb", + f"--year={STRING_YEAR_2020}", + f"--email={EMAIL}", + f"--file_path={FILE_PATH}", + f"--region={REGION}", + f"--key={API_KEY}", + f"--method={METHOD}", +] + +SOLAR_DATA_NSRDB_ARG_LIST_SHORT_FLAGS = [ + "solar_data_nsrdb", + f"-y={STRING_YEAR_2020}", + f"-e={EMAIL}", + f"-fp={FILE_PATH}", + f"-r={REGION}", + f"-k={API_KEY}", + f"-m={METHOD}", +] + +ALL_ARGUMENTS = [ + WIND_DATA_RAP_ARG_LIST_FULL_FLAGS, + WIND_DATA_RAP_ARG_LIST_SHORT_FLAGS, + SOLAR_DATA_GA_ARG_LIST_FULL_FLAGS, + SOLAR_DATA_GA_ARG_LIST_SHORT_FLAGS, + SOLAR_DATA_NSRDB_ARG_LIST_FULL_FLAGS, + SOLAR_DATA_NSRDB_ARG_LIST_SHORT_FLAGS, +] + -@pytest.mark.parametrize( - "args", [WIND_DATA_ARG_LIST_FULL_FLAGS, WIND_DATA_ARG_LIST_SHORT_FLAGS] -) -def test_parser_wind_data(args): +@pytest.mark.parametrize("args", ALL_ARGUMENTS) +def test_parser(args): parser = generate_parser() - result = parser.parse_args(args) - assert START_DATE == result.start_date - assert END_DATE == result.end_date - assert REGION in result.region - assert FILE_PATH == result.file_path + parser.parse_args(args) -@pytest.mark.parametrize( - "args", [WIND_DATA_ARG_LIST_FULL_FLAGS, WIND_DATA_ARG_LIST_SHORT_FLAGS] -) -def test_parser_wind_data_missing_flags(args): +@pytest.mark.parametrize("args", ALL_ARGUMENTS) +def test_parser_missing_flags(args): parser = generate_parser() for arg in args: bad_arg_list = args.copy() diff --git a/prereise/cli/helpers.py b/prereise/cli/helpers.py index 8bde8489c..3fe81f01c 100644 --- a/prereise/cli/helpers.py +++ b/prereise/cli/helpers.py @@ -2,7 +2,7 @@ import os from datetime import datetime -from prereise.cli.constants import DATE_FMT +from prereise.cli.constants import DATE_FMT, YEAR_FMT def validate_date(date_string): @@ -15,6 +15,16 @@ def validate_date(date_string): return date_string +def validate_year(year_string): + """Helper function to validate year strings + + :param str year_string: year in string format to be validated + :return: (*str*) -- validated year string + """ + datetime.strptime(year_string, YEAR_FMT) + return year_string + + def validate_file_path(file_path): """Helper function to validate file paths @@ -32,17 +42,16 @@ def validate_file_path(file_path): return file_path -def add_data_source_to_download_parser(data_source, parser): +def add_data_source_to_download_parser(data_source, subparsers): """Helper function that adds an additional source of data that the user can interact with and download via the command line tool :param prereise.cli.data_sources.data_source.DataSource data_source: an instance of a class that implements the abstract class DataSource - :param argparse.ArgumentParser parser: parser that implements command + :param argparse.ArgumentParser subparsers: subparser object that implements command line interface functionality """ - subparsers = parser.add_subparsers() subparser = subparsers.add_parser( data_source.command_name, help=data_source.command_help ) diff --git a/prereise/cli/tests/test_helpers.py b/prereise/cli/tests/test_helpers.py index a5591a136..0e2d7a30c 100644 --- a/prereise/cli/tests/test_helpers.py +++ b/prereise/cli/tests/test_helpers.py @@ -6,6 +6,7 @@ add_data_source_to_download_parser, validate_date, validate_file_path, + validate_year, ) @@ -31,6 +32,16 @@ def test_validate_date_bad_date(): validate_date("2020-01-49") +def test_validate_year(): + year = "2020" + assert validate_year(year) == year + + +def test_validate_year_bad_year(): + with pytest.raises(ValueError): + validate_year("2020233") + + @patch("prereise.cli.helpers.os") def test_validate_file_path(os): file_path = "somefilepath" @@ -57,12 +68,10 @@ def test_validate_file_path_is_direcotry(os): def test_add_data_source_to_download_parser(data_source): - parser = MagicMock() subparsers = MagicMock() subparser = MagicMock() subparsers.add_parser.return_value = subparser - parser.add_subparsers.return_value = subparsers - add_data_source_to_download_parser(data_source, parser) + add_data_source_to_download_parser(data_source, subparsers) subparsers.add_parser.assert_called_with( data_source.command_name, help=data_source.command_help ) From ec6f4bd67d04cfbc5cc577a83220e8e2e2c35796 Mon Sep 17 00:00:00 2001 From: jon-hagg <66005238+jon-hagg@users.noreply.github.com> Date: Fri, 9 Jul 2021 16:24:29 -0700 Subject: [PATCH 19/61] chore: update packages with dependency on urllib3 (#188) --- Pipfile | 6 +- Pipfile.lock | 489 ++++++++++++++++++++++++++++++++--------------- requirements.txt | 6 +- 3 files changed, 345 insertions(+), 156 deletions(-) diff --git a/Pipfile b/Pipfile index 4ded4426c..df2778db9 100644 --- a/Pipfile +++ b/Pipfile @@ -11,12 +11,12 @@ pytest-cov = "*" [packages] bokeh = "==2.0.2" -h5pyd = "==0.3.3" +h5pyd = "~=0.8" matplotlib = "~=3.3" -numpy = "~=1.19" +numpy = "~=1.20" pandas = "~=1.1.2" python-dateutil = "==2.7.5" -requests = "~=2.24.0" +requests = "~=2.25" scipy = "~=1.6" tqdm = "==4.29.1" xlrd = "==1.2.0" diff --git a/Pipfile.lock b/Pipfile.lock index 0fb7161d1..c0dcb505e 100644 --- a/Pipfile.lock +++ b/Pipfile.lock @@ -1,7 +1,7 @@ { "_meta": { "hash": { - "sha256": "b56ab9869068571dd50d58f3e38dafc75f289e9e531f0b10945f15154704dd38" + "sha256": "150ca8d367ec2dddcb9b8cc69d537b748407f19e87c55f8d579d8d099059975b" }, "pipfile-spec": 6, "requires": {}, @@ -14,6 +14,13 @@ ] }, "default": { + "adal": { + "hashes": [ + "sha256:2a7451ed7441ddbc57703042204a3e30ef747478eea022c70f789fc7f084bc3d", + "sha256:d74f45b81317454d96e982fd1c50e6fb5c99ac2223728aea8764433a39f566f1" + ], + "version": "==1.2.7" + }, "bcrypt": { "hashes": [ "sha256:5b93c1726e50a93a033c36e5ca7fdcd29a5c7395af50a6892f5d9e7c6cfbfb29", @@ -34,6 +41,14 @@ "index": "pypi", "version": "==2.0.2" }, + "cachetools": { + "hashes": [ + "sha256:2cc0b89715337ab6dbba85b5b50effe2b0c74e035d83ee8ed637cf52f12ae001", + "sha256:61b5ed1e22a0924aed1d23b478f37e8d52549ff8a961de2909c69bf950020cff" + ], + "markers": "python_version ~= '3.5'", + "version": "==4.2.2" + }, "certifi": { "hashes": [ "sha256:2bbf76fd432960138b3ef6dda3dde0544f27cbf8546c458e60baf371917ba9ee", @@ -43,57 +58,48 @@ }, "cffi": { "hashes": [ - "sha256:005a36f41773e148deac64b08f233873a4d0c18b053d37da83f6af4d9087b813", - "sha256:04c468b622ed31d408fea2346bec5bbffba2cc44226302a0de1ade9f5ea3d373", - "sha256:06d7cd1abac2ffd92e65c0609661866709b4b2d82dd15f611e602b9b188b0b69", - "sha256:06db6321b7a68b2bd6df96d08a5adadc1fa0e8f419226e25b2a5fbf6ccc7350f", - 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a/requirements.txt +++ b/requirements.txt @@ -1,13 +1,13 @@ bokeh==2.0.2 -h5pyd==0.3.3 +h5pyd~=0.8 matplotlib~=3.3 netCDF4==1.5.4 -numpy~=1.19 +numpy~=1.20 pandas~=1.1.2 -e ../PowerSimData pyproj==2.6.1.post1 python-dateutil==2.7.5 -requests~=2.24.0 +requests~=2.25 scipy~=1.6 tqdm==4.29.1 xlrd==1.2.0 From 383e676d99f5c56b5c1cacaadc2fa215a791098c Mon Sep 17 00:00:00 2001 From: George Tong Date: Wed, 7 Jul 2021 17:43:44 -0700 Subject: [PATCH 20/61] feat: add ability to select grid model to cli --- prereise/cli/constants.py | 2 + prereise/cli/data_sources/solar_data.py | 39 ++++++++++++++++--- prereise/cli/data_sources/tests/conftest.py | 1 + .../cli/data_sources/tests/test_solar_data.py | 5 +++ .../cli/data_sources/tests/test_wind_data.py | 4 ++ prereise/cli/data_sources/wind_data.py | 17 ++++++-- prereise/cli/helpers.py | 23 +++++++++++ prereise/cli/tests/test_helpers.py | 21 ++++++++++ 8 files changed, 104 insertions(+), 8 deletions(-) diff --git a/prereise/cli/constants.py b/prereise/cli/constants.py index a6f566e4d..0862e44b1 100644 --- a/prereise/cli/constants.py +++ b/prereise/cli/constants.py @@ -3,4 +3,6 @@ START_DATE_HELP_STRING = "The start date for the data download in format 'YYYY-MM-DD'" END_DATE_HELP_STRING = "The end date for the data download in format 'YYYY-MM-DD'" FILE_PATH_HELP_STRING = "The file path to store the downloaded data. Must include filename and .pkl file extension." +GRID_MODEL_HELP_STRING = "A .mat file path for a grid model or a string supported by powersimdata.input.grid.Grid.SUPPORTED_MODELS" +GRID_MODEL_DEFAULT = "usa_tamu" REGION_CHOICES = ["Texas", "Eastern", "Western"] diff --git a/prereise/cli/data_sources/solar_data.py b/prereise/cli/data_sources/solar_data.py index c65541f32..a4b378622 100644 --- a/prereise/cli/data_sources/solar_data.py +++ b/prereise/cli/data_sources/solar_data.py @@ -6,11 +6,18 @@ DATE_FMT, END_DATE_HELP_STRING, FILE_PATH_HELP_STRING, + GRID_MODEL_DEFAULT, + GRID_MODEL_HELP_STRING, REGION_CHOICES, START_DATE_HELP_STRING, ) from prereise.cli.data_sources.data_source import DataSource -from prereise.cli.helpers import validate_date, validate_file_path, validate_year +from prereise.cli.helpers import ( + validate_date, + validate_file_path, + validate_grid_model, + validate_year, +) from prereise.gather.solardata.ga_wind import ga_wind from prereise.gather.solardata.nsrdb import naive, sam @@ -76,9 +83,18 @@ def extract_arguments(self): "type": str, "help": API_KEY_HELP_STRING, }, + { + "command_flags": ["--grid_model", "-gm"], + "required": False, + "default": GRID_MODEL_DEFAULT, + "type": validate_grid_model, + "help": GRID_MODEL_HELP_STRING, + }, ] - def extract(self, region, start_date, end_date, file_path, key, **kwargs): + def extract( + self, region, start_date, end_date, file_path, key, grid_model, **kwargs + ): """See :py:func:`prereise.cli.data_sources.data_source.DataSource.extract` :param list region: list of regions to download data for @@ -86,11 +102,13 @@ def extract(self, region, start_date, end_date, file_path, key, **kwargs): :param str end_date: date designating when to end the data download :param str file_path: file location on local filesystem on where to store the data :param str key: API key that can be requested at https://developer.nrel.gov/signup/ + :param str grid_model: .mat file path for a grid model or a string supported by + `powersimdata.input.grid.Grid.SUPPORTED_MODELS` """ assert datetime.strptime(start_date, DATE_FMT) <= datetime.strptime( end_date, DATE_FMT ) - grid = Grid(region) + grid = Grid(region, source=grid_model) solar_plants = grid.plant.groupby("type").get_group("solar") data = ga_wind.retrieve_data( solar_plants, key, start_date=start_date, end_date=end_date @@ -159,9 +177,18 @@ def extract_arguments(self): "type": str, "help": API_KEY_HELP_STRING, }, + { + "command_flags": ["--grid_model", "-gm"], + "required": False, + "default": GRID_MODEL_DEFAULT, + "type": validate_grid_model, + "help": GRID_MODEL_HELP_STRING, + }, ] - def extract(self, region, method, year, file_path, email, key, **kwargs): + def extract( + self, region, method, year, file_path, email, key, grid_model, **kwargs + ): """See :py:func:`prereise.cli.data_sources.data_source.DataSource.extract` :param list region: list of regions to download data for @@ -170,8 +197,10 @@ def extract(self, region, method, year, file_path, email, key, **kwargs): :param str file_path: file location on local filesystem on where to store the data :param str email: email used to sign up at https://developer.nrel.gov/signup/ :param str key: API key that can be requested at https://developer.nrel.gov/signup/ + :param str grid_model: .mat file path for a grid model or a string supported by + `powersimdata.input.grid.Grid.SUPPORTED_MODELS` """ - grid = Grid(region) + grid = Grid(region, source=grid_model) solar_plants = grid.plant.groupby("type").get_group("solar") if method == NAIVE_STRING: data = naive.retrieve_data(solar_plants, email, key, year) diff --git a/prereise/cli/data_sources/tests/conftest.py b/prereise/cli/data_sources/tests/conftest.py index c85dfd9ce..9c0f40396 100644 --- a/prereise/cli/data_sources/tests/conftest.py +++ b/prereise/cli/data_sources/tests/conftest.py @@ -6,3 +6,4 @@ API_KEY = "FAKE_API_KEY" STRING_YEAR_2020 = "2020" INVALID_METHOD = "gibberish" +VALID_GRID_MODEL = "usa_tamu" diff --git a/prereise/cli/data_sources/tests/test_solar_data.py b/prereise/cli/data_sources/tests/test_solar_data.py index d0e47bbdd..5b2a3a5eb 100644 --- a/prereise/cli/data_sources/tests/test_solar_data.py +++ b/prereise/cli/data_sources/tests/test_solar_data.py @@ -17,6 +17,7 @@ STRING_DATE_2021_12_1, STRING_YEAR_2020, TEXAS_REGION_LIST, + VALID_GRID_MODEL, ) @@ -38,6 +39,7 @@ def test_solar_data_ga_end_date_before_start_date(solar_data_ga_object): STRING_DATE_2021_5_1, CURRENT_DIRECTORY_FILEPATH, API_KEY, + VALID_GRID_MODEL, ) @@ -54,6 +56,7 @@ def test_solar_data_ga_happy_path(grid, ga_wind, solar_data_ga_object): STRING_DATE_2021_12_1, CURRENT_DIRECTORY_FILEPATH, API_KEY, + VALID_GRID_MODEL, ) ga_wind.retrieve_data.assert_called_with( solar_farms, @@ -73,6 +76,7 @@ def test_solar_data_nsrdb_invalid_method(solar_data_nsrdb_object): CURRENT_DIRECTORY_FILEPATH, EMAIL, API_KEY, + VALID_GRID_MODEL, ) @@ -99,6 +103,7 @@ def test_solar_data_nsrdb_happy_path(grid, solar_data_nsrdb_object): CURRENT_DIRECTORY_FILEPATH, EMAIL, API_KEY, + VALID_GRID_MODEL, ) method.retrieve_data.assert_called_with( solar_farms, EMAIL, API_KEY, STRING_YEAR_2020 diff --git a/prereise/cli/data_sources/tests/test_wind_data.py b/prereise/cli/data_sources/tests/test_wind_data.py index 56eafecd1..eaf8ed273 100644 --- a/prereise/cli/data_sources/tests/test_wind_data.py +++ b/prereise/cli/data_sources/tests/test_wind_data.py @@ -7,6 +7,7 @@ STRING_DATE_2021_5_1, STRING_DATE_2021_12_1, TEXAS_REGION_LIST, + VALID_GRID_MODEL, ) from prereise.cli.data_sources.wind_data import WindDataRapidRefresh @@ -23,6 +24,7 @@ def test_winddata_end_date_before_start_date(wind_data_object): STRING_DATE_2021_12_1, STRING_DATE_2021_5_1, CURRENT_DIRECTORY_FILEPATH, + VALID_GRID_MODEL, ) @@ -40,6 +42,7 @@ def test_winddata_happy_path(grid, rap, wind_data_object): STRING_DATE_2021_5_1, STRING_DATE_2021_12_1, CURRENT_DIRECTORY_FILEPATH, + VALID_GRID_MODEL, ) rap.retrieve_data.assert_called_with( wind_farms, start_date=STRING_DATE_2021_5_1, end_date=STRING_DATE_2021_12_1 @@ -62,6 +65,7 @@ def test_winddata_missing_files(logging, grid, rap, wind_data_object): STRING_DATE_2021_5_1, STRING_DATE_2021_12_1, CURRENT_DIRECTORY_FILEPATH, + VALID_GRID_MODEL, ) rap.retrieve_data.assert_called_with( wind_farms, start_date=STRING_DATE_2021_5_1, end_date=STRING_DATE_2021_12_1 diff --git a/prereise/cli/data_sources/wind_data.py b/prereise/cli/data_sources/wind_data.py index a124ebe6c..cef4884c8 100644 --- a/prereise/cli/data_sources/wind_data.py +++ b/prereise/cli/data_sources/wind_data.py @@ -7,11 +7,13 @@ DATE_FMT, END_DATE_HELP_STRING, FILE_PATH_HELP_STRING, + GRID_MODEL_DEFAULT, + GRID_MODEL_HELP_STRING, REGION_CHOICES, START_DATE_HELP_STRING, ) from prereise.cli.data_sources.data_source import DataSource -from prereise.cli.helpers import validate_date, validate_file_path +from prereise.cli.helpers import validate_date, validate_file_path, validate_grid_model from prereise.gather.winddata.rap import rap @@ -64,21 +66,30 @@ def extract_arguments(self): "type": validate_file_path, "help": FILE_PATH_HELP_STRING, }, + { + "command_flags": ["--grid_model", "-gm"], + "required": False, + "default": GRID_MODEL_DEFAULT, + "type": validate_grid_model, + "help": GRID_MODEL_HELP_STRING, + }, ] - def extract(self, region, start_date, end_date, file_path, **kwargs): + def extract(self, region, start_date, end_date, file_path, grid_model, **kwargs): """See :py:func:`prereise.cli.data_sources.data_source.DataSource.extract` :param list region: list of regions to download wind farm data for :param str start_date: date designating when to start the data download :param str end_date: date designating when to end the data download :param str file_path: file location on local filesystem on where to store the data + :param str grid_model: .mat file path for a grid model or a string supported by + `powersimdata.input.grid.Grid.SUPPORTED_MODELS` """ assert datetime.strptime(start_date, DATE_FMT) <= datetime.strptime( end_date, DATE_FMT ) - grid = Grid(region) + grid = Grid(region, source=grid_model) wind_farms = grid.plant.groupby("type").get_group("wind") data, missing = rap.retrieve_data( wind_farms, start_date=start_date, end_date=end_date diff --git a/prereise/cli/helpers.py b/prereise/cli/helpers.py index 3fe81f01c..b73c29a12 100644 --- a/prereise/cli/helpers.py +++ b/prereise/cli/helpers.py @@ -2,9 +2,32 @@ import os from datetime import datetime +from powersimdata.input.grid import Grid + from prereise.cli.constants import DATE_FMT, YEAR_FMT +def validate_grid_model(grid_model): + """Helper function to validate grid model parameter. Does + NOT validate the actual contents of the grid file. + + :param str grid_model: file path to a .mat file that represents + the grid, or a supported default grid selection + :return: (*str*) -- validated grid model + """ + if grid_model in Grid.SUPPORTED_MODELS: + return grid_model + + if grid_model.endswith(".mat") and os.path.isfile(grid_model): + return grid_model + + all_supported_models = ", ".join(Grid.SUPPORTED_MODELS) + + raise ValueError( + f"grid_model must be either a valid .mat file path or a valid selection of {all_supported_models}" + ) + + def validate_date(date_string): """Helper function to validate date strings diff --git a/prereise/cli/tests/test_helpers.py b/prereise/cli/tests/test_helpers.py index 0e2d7a30c..ac086f8a1 100644 --- a/prereise/cli/tests/test_helpers.py +++ b/prereise/cli/tests/test_helpers.py @@ -1,14 +1,18 @@ from unittest.mock import MagicMock, patch import pytest +from powersimdata.input.grid import Grid from prereise.cli.helpers import ( add_data_source_to_download_parser, validate_date, validate_file_path, + validate_grid_model, validate_year, ) +INVALID_GRID_MODEL = "INVALID_GRID_MODEL" + @pytest.fixture def data_source(): @@ -22,6 +26,23 @@ def data_source(): return data_source_mock +def test_validate_grid_model(): + for grid_model in list(Grid.SUPPORTED_MODELS): + assert validate_grid_model(grid_model) == grid_model + + +def test_validate_grid_model_mat_file(tmp_path): + tmp_mat_file = tmp_path / "tmp_file.mat" + tmp_mat_file.write_text("CONTENT") + path = str(tmp_mat_file) + assert validate_grid_model(path) == path + + +def test_validate_grid_model_bad_value(): + with pytest.raises(ValueError): + validate_grid_model(INVALID_GRID_MODEL) + + def test_validate_date(): date = "2020-01-03" assert validate_date(date) == date From e2c79f2b74cc013aac6925297330c1a713ac1369 Mon Sep 17 00:00:00 2001 From: George Tong Date: Sat, 10 Jul 2021 18:19:57 -0700 Subject: [PATCH 21/61] bug: remove cli support for .mat files --- prereise/cli/constants.py | 4 +++- prereise/cli/data_sources/solar_data.py | 11 +++-------- prereise/cli/data_sources/wind_data.py | 4 ++-- prereise/cli/helpers.py | 23 ----------------------- prereise/cli/tests/test_helpers.py | 21 --------------------- 5 files changed, 8 insertions(+), 55 deletions(-) diff --git a/prereise/cli/constants.py b/prereise/cli/constants.py index 0862e44b1..6e76aaa77 100644 --- a/prereise/cli/constants.py +++ b/prereise/cli/constants.py @@ -3,6 +3,8 @@ START_DATE_HELP_STRING = "The start date for the data download in format 'YYYY-MM-DD'" END_DATE_HELP_STRING = "The end date for the data download in format 'YYYY-MM-DD'" FILE_PATH_HELP_STRING = "The file path to store the downloaded data. Must include filename and .pkl file extension." -GRID_MODEL_HELP_STRING = "A .mat file path for a grid model or a string supported by powersimdata.input.grid.Grid.SUPPORTED_MODELS" +GRID_MODEL_HELP_STRING = ( + "A string supported by powersimdata.input.grid.Grid.SUPPORTED_MODELS" +) GRID_MODEL_DEFAULT = "usa_tamu" REGION_CHOICES = ["Texas", "Eastern", "Western"] diff --git a/prereise/cli/data_sources/solar_data.py b/prereise/cli/data_sources/solar_data.py index a4b378622..d3842905c 100644 --- a/prereise/cli/data_sources/solar_data.py +++ b/prereise/cli/data_sources/solar_data.py @@ -12,12 +12,7 @@ START_DATE_HELP_STRING, ) from prereise.cli.data_sources.data_source import DataSource -from prereise.cli.helpers import ( - validate_date, - validate_file_path, - validate_grid_model, - validate_year, -) +from prereise.cli.helpers import validate_date, validate_file_path, validate_year from prereise.gather.solardata.ga_wind import ga_wind from prereise.gather.solardata.nsrdb import naive, sam @@ -87,7 +82,7 @@ def extract_arguments(self): "command_flags": ["--grid_model", "-gm"], "required": False, "default": GRID_MODEL_DEFAULT, - "type": validate_grid_model, + "choices": list(Grid.SUPPORTED_MODELS), "help": GRID_MODEL_HELP_STRING, }, ] @@ -181,7 +176,7 @@ def extract_arguments(self): "command_flags": ["--grid_model", "-gm"], "required": False, "default": GRID_MODEL_DEFAULT, - "type": validate_grid_model, + "choices": list(Grid.SUPPORTED_MODELS), "help": GRID_MODEL_HELP_STRING, }, ] diff --git a/prereise/cli/data_sources/wind_data.py b/prereise/cli/data_sources/wind_data.py index cef4884c8..f3465174f 100644 --- a/prereise/cli/data_sources/wind_data.py +++ b/prereise/cli/data_sources/wind_data.py @@ -13,7 +13,7 @@ START_DATE_HELP_STRING, ) from prereise.cli.data_sources.data_source import DataSource -from prereise.cli.helpers import validate_date, validate_file_path, validate_grid_model +from prereise.cli.helpers import validate_date, validate_file_path from prereise.gather.winddata.rap import rap @@ -70,7 +70,7 @@ def extract_arguments(self): "command_flags": ["--grid_model", "-gm"], "required": False, "default": GRID_MODEL_DEFAULT, - "type": validate_grid_model, + "choices": list(Grid.SUPPORTED_MODELS), "help": GRID_MODEL_HELP_STRING, }, ] diff --git a/prereise/cli/helpers.py b/prereise/cli/helpers.py index b73c29a12..3fe81f01c 100644 --- a/prereise/cli/helpers.py +++ b/prereise/cli/helpers.py @@ -2,32 +2,9 @@ import os from datetime import datetime -from powersimdata.input.grid import Grid - from prereise.cli.constants import DATE_FMT, YEAR_FMT -def validate_grid_model(grid_model): - """Helper function to validate grid model parameter. Does - NOT validate the actual contents of the grid file. - - :param str grid_model: file path to a .mat file that represents - the grid, or a supported default grid selection - :return: (*str*) -- validated grid model - """ - if grid_model in Grid.SUPPORTED_MODELS: - return grid_model - - if grid_model.endswith(".mat") and os.path.isfile(grid_model): - return grid_model - - all_supported_models = ", ".join(Grid.SUPPORTED_MODELS) - - raise ValueError( - f"grid_model must be either a valid .mat file path or a valid selection of {all_supported_models}" - ) - - def validate_date(date_string): """Helper function to validate date strings diff --git a/prereise/cli/tests/test_helpers.py b/prereise/cli/tests/test_helpers.py index ac086f8a1..0e2d7a30c 100644 --- a/prereise/cli/tests/test_helpers.py +++ b/prereise/cli/tests/test_helpers.py @@ -1,18 +1,14 @@ from unittest.mock import MagicMock, patch import pytest -from powersimdata.input.grid import Grid from prereise.cli.helpers import ( add_data_source_to_download_parser, validate_date, validate_file_path, - validate_grid_model, validate_year, ) -INVALID_GRID_MODEL = "INVALID_GRID_MODEL" - @pytest.fixture def data_source(): @@ -26,23 +22,6 @@ def data_source(): return data_source_mock -def test_validate_grid_model(): - for grid_model in list(Grid.SUPPORTED_MODELS): - assert validate_grid_model(grid_model) == grid_model - - -def test_validate_grid_model_mat_file(tmp_path): - tmp_mat_file = tmp_path / "tmp_file.mat" - tmp_mat_file.write_text("CONTENT") - path = str(tmp_mat_file) - assert validate_grid_model(path) == path - - -def test_validate_grid_model_bad_value(): - with pytest.raises(ValueError): - validate_grid_model(INVALID_GRID_MODEL) - - def test_validate_date(): date = "2020-01-03" assert validate_date(date) == date From 8fd6096d3b1d151568a3db3952ab86798356a2e9 Mon Sep 17 00:00:00 2001 From: BainanXia Date: Fri, 2 Jul 2021 11:23:03 -0700 Subject: [PATCH 22/61] data: add data file that provides a list of counties for each BA --- prereise/gather/data/BA_County_map.json | 3221 +++++++++++++++++++++++ 1 file changed, 3221 insertions(+) create mode 100644 prereise/gather/data/BA_County_map.json diff --git a/prereise/gather/data/BA_County_map.json b/prereise/gather/data/BA_County_map.json new file mode 100644 index 000000000..eee98380d --- /dev/null +++ b/prereise/gather/data/BA_County_map.json @@ -0,0 +1,3221 @@ +{ + "ISNE": [ + "Androscoggin__ME", + "Kennebec__ME", + "Oxford__ME", + "Piscataquis__ME", + "Aroostook__ME", + "Washington__ME", + "Penobscot__ME", + "Cumberland__ME", + "Sagadahoc__ME", + "York__ME", + "Franklin__ME", + "Hancock__ME", + "Waldo__ME", + "Somerset__ME", + "Knox__ME", + "Lincoln__ME", + "Carroll__NH", + "Strafford__NH", + "Rockingham__NH", + "Belknap__NH", + "Merrimack__NH", + "Cheshire__NH", + "Hillsborough__NH", + "Windham__VT", + "Franklin__MA", + "Coos__NH", + "Essex__VT", + "Grafton__NH", + "Sullivan__NH", + "Middlesex__MA", + "Essex__MA", + "Rutland__VT", + "Addison__VT", + "Chittenden__VT", + "Bennington__VT", + "Berkshire__MA", + "Caledonia__VT", + "Orleans__VT", + "Orange__VT", + "Grand Isle__VT", + "Washington__VT", + "Franklin__VT", + "Lamoille__VT", + "Windsor__VT", + "Barnstable__MA", + "Plymouth__MA", + "Litchfield__CT", + "Bristol__MA", + "Newport__RI", + "Norfolk__MA", + "Kent__RI", + "Providence__RI", + "Suffolk__MA", + "Hampshire__MA", + "Hartford__CT", + "Hampden__MA", + "Tolland__CT", + "Worcester__MA", + "Windham__CT", + "Bristol__RI", + "Washington__RI", + "New London__CT", + "Fairfield__CT", + "New Haven__CT", + "Middlesex__CT", + "Dukes__MA", + "Nantucket__MA" + ], + "NYIS": [ + "Washington__NY", + "Westchester__NY", + "Nassau__NY", + "Putnam__NY", + "Suffolk__NY", + "Bronx__NY", + "New York__NY", + "Queens__NY", + "Dutchess__NY", + "Orange__NY", + "Ulster__NY", + "Kings__NY", + "Richmond__NY", + "Sullivan__NY", + "Rockland__NY", + "Albany__NY", + "Rensselaer__NY", + "Saratoga__NY", + "Schenectady__NY", + "Greene__NY", + "Schoharie__NY", + "Steuben__NY", + "Allegany__NY", + "Wyoming__NY", + "Cattaraugus__NY", + "Chenango__NY", + "Tioga__NY", + "Broome__NY", + "Delaware__NY", + "Cortland__NY", + "Erie__NY", + "Chautauqua__NY", + "Cayuga__NY", + "Onondaga__NY", + "Oswego__NY", + "Tompkins__NY", + "Wayne__NY", + "Schuyler__NY", + "Chemung__NY", + "Madison__NY", + "Otsego__NY", + "Essex__NY", + "Clinton__NY", + "Franklin__NY", + "Columbia__NY", + "Genesee__NY", + "Niagara__NY", + "Warren__NY", + "Montgomery__NY", + "Fulton__NY", + "Herkimer__NY", + "Hamilton__NY", + "Monroe__NY", + "Livingston__NY", + "Lewis__NY", + "Oneida__NY", + "Jefferson__NY", + "St. Lawrence__NY", + "Ontario__NY", + "Orleans__NY", + "Seneca__NY", + "Yates__NY" + ], + "PJM": [ + "Bergen__NJ", + "Hudson__NJ", + "Essex__NJ", + "Monmouth__NJ", + "Passaic__NJ", + "Sussex__NJ", + "Union__NJ", + "Middlesex__NJ", + "Pike__PA", + "Wayne__PA", + "McKean__PA", + "Potter__PA", + "Susquehanna__PA", + "Warren__PA", + "Bradford__PA", + "Tioga__PA", + "Atlantic__NJ", + "Burlington__NJ", + "Camden__NJ", + "Cumberland__NJ", + "Gloucester__NJ", + "Cape May__NJ", + "Philadelphia__PA", + "Bucks__PA", + "Mercer__NJ", + "Ocean__NJ", + "Sussex__DE", + "Morris__NJ", + "Delaware__PA", + "Salem__NJ", + "Hunterdon__NJ", + "Warren__NJ", + "Somerset__NJ", + "New Castle__DE", + "Northampton__PA", + "Adams__PA", + "York__PA", + "Franklin__PA", + "Carroll__MD", + "Lehigh__PA", + "Berks__PA", + "Montgomery__PA", + "Chester__PA", + "Lancaster__PA", + "Lebanon__PA", + "Wyoming__PA", + "Carbon__PA", + "Monroe__PA", + "Luzerne__PA", + "Schuylkill__PA", + "Centre__PA", + "Cecil__MD", + "Clinton__PA", + "Lycoming__PA", + "Columbia__PA", + "Northumberland__PA", + "Montour__PA", + "Cumberland__PA", + "Dauphin__PA", + "Perry__PA", + "Juniata__PA", + "Mifflin__PA", + "Snyder__PA", + "Lackawanna__PA", + "Union__PA", + "Sullivan__PA", + "Baltimore__MD", + "Allegheny__PA", + "Beaver__PA", + "Washington__PA", + "Butler__PA", + "Westmoreland__PA", + "Armstrong__PA", + "Jefferson__PA", + "Clarion__PA", + "Indiana__PA", + "Columbiana__OH", + "Lawrence__PA", + "Hancock__WV", + "Bedford__PA", + "Fulton__PA", + "Blair__PA", + "Allegany__MD", + "Cambria__PA", + "Huntingdon__PA", + "Venango__PA", + "Mercer__PA", + "Clearfield__PA", + "Somerset__PA", + "Cameron__PA", + "Forest__PA", + "Erie__PA", + "Crawford__PA", + "Ashtabula__OH", + "Elk__PA", + "Fayette__PA", + "Greene__PA", + "Preston__WV", + "Mahoning__OH", + "Trumbull__OH", + "Garrett__MD", + "Ohio__WV", + "Kent__DE", + "Wicomico__MD", + "Worcester__MD", + "Mineral__WV", + "Hampshire__WV", + "Anne Arundel__MD", + "Prince George's__MD", + "Calvert__MD", + "Howard__MD", + "Talbot__MD", + "Baltimore City__MD", + "Harford__MD", + "Kent__MD", + "Caroline__MD", + "Queen Anne's__MD", + "Frederick__MD", + "Montgomery__MD", + "Charles__MD", + "St. Mary's__MD", + "King George__VA", + "District of Columbia__DC", + "Alexandria City__VA", + "Arlington__VA", + "Fairfax__VA", + "Dorchester__MD", + "Loudoun__VA", + "Jefferson__WV", + "Somerset__MD", + "Washington__MD", + "Morgan__WV", + "Berkeley__WV", + "Albemarle__VA", + "Madison__VA", + "Fluvanna__VA", + "Orange__VA", + "Louisa__VA", + "Greene__VA", + "Buckingham__VA", + "Alleghany__VA", + "Botetourt__VA", + "Prince Edward__VA", + "Amherst__VA", + "Nelson__VA", + "Appomattox__VA", + "Campbell__VA", + "Lynchburg City__VA", + "Rockingham__VA", + "Augusta__VA", + "Rockbridge__VA", + "Staunton City__VA", + "Waynesboro City__VA", + "Bath__VA", + "Bedford__VA", + "Bedford City__VA", + "Franklin__VA", + "Bland__VA", + "Pulaski__VA", + "Giles__VA", + "Roanoke__VA", + "Roanoke City__VA", + "Salem City__VA", + "Craig__VA", + "Washington__VA", + "Bristol City__VA", + "Mecklenburg__VA", + "Brunswick__VA", + "Buchanan__VA", + "Dickenson__VA", + "Russell__VA", + "Cumberland__VA", + "Pittsylvania__VA", + "Charlotte__VA", + "Patrick__VA", + "Wythe__VA", + "Carroll__VA", + "Grayson__VA", + "Floyd__VA", + "Lunenburg__VA", + "Clarke__VA", + "Warren__VA", + "Frederick__VA", + "Fauquier__VA", + "Rappahannock__VA", + "Culpeper__VA", + "Wise__VA", + "Montgomery__VA", + "Radford City__VA", + "Henry__VA", + "Goochland__VA", + "Powhatan__VA", + "Halifax__VA", + "Highland__VA", + "Scott__VA", + "Page__VA", + "Nottoway__VA", + "Shenandoah__VA", + "Tazewell__VA", + "Smyth__VA", + "Mercer__WV", + "Accomack__VA", + "Northampton__VA", + "Amelia__VA", + "Chesterfield__VA", + "Falls Church City__VA", + "Dinwiddie__VA", + "Greensville__VA", + "Emporia City__VA", + "Caroline__VA", + "Spotsylvania__VA", + "Fredericksburg City__VA", + "Charles City__VA", + "Henrico__VA", + "New Kent__VA", + "York__VA", + "Surry__VA", + "James City__VA", + "Suffolk City__VA", + "Chesapeake City__VA", + "Portsmouth City__VA", + "Colonial Heights City__VA", + "Richmond City__VA", + "Prince George__VA", + "Petersburg City__VA", + "Sussex__VA", + "Essex__VA", + "King and Queen__VA", + "Fairfax City__VA", + "Prince William__VA", + "Stafford__VA", + "Southampton__VA", + "Gloucester__VA", + "Mathews__VA", + "Hanover__VA", + "Hampton City__VA", + "Newport News City__VA", + "Norfolk City__VA", + "Hopewell City__VA", + "Isle of Wight__VA", + "King William__VA", + "Northumberland__VA", + "Lancaster__VA", + "Manassas City__VA", + "Manassas Park City__VA", + "Middlesex__VA", + "Richmond__VA", + "Poquoson City__VA", + "Virginia Beach City__VA", + "Currituck__NC", + "Westmoreland__VA", + "Hyde__NC", + "Martin__NC", + "Hertford__NC", + "Bertie__NC", + "Pasquotank__NC", + "Perquimans__NC", + "Camden__NC", + "Chowan__NC", + "Dare__NC", + "Gates__NC", + "Tyrrell__NC", + "Northampton__NC", + "Washington__NC", + "Clinton__KY", + "McCreary__KY", + "Adair__KY", + "Green__KY", + "Metcalfe__KY", + "Taylor__KY", + "Casey__KY", + "Russell__KY", + "Anderson__KY", + "Mercer__KY", + "Barren__KY", + "Hart__KY", + "Montgomery__KY", + "Bath__KY", + "Menifee__KY", + "Boone__KY", + "Grant__KY", + "Kenton__KY", + "Hamilton__OH", + "Gallatin__KY", + "Nicholas__KY", + "Harrison__KY", + "Scott__KY", + "Bourbon__KY", + "Boyd__KY", + "Lawrence__OH", + "Greenup__KY", + "Wayne__WV", + "Boyle__KY", + "Bracken__KY", + "Robertson__KY", + "Pendleton__KY", + "Clermont__OH", + "Lee__KY", + "Owsley__KY", + "Wolfe__KY", + "Breathitt__KY", + "Hardin__KY", + "Nelson__KY", + "Bullitt__KY", + "Spencer__KY", + "Campbell__KY", + "Trimble__KY", + "Henry__KY", + "Carter__KY", + "Rowan__KY", + "Elliott__KY", + "Lewis__KY", + "Lawrence__KY", + "Lincoln__KY", + "Madison__KY", + "Jessamine__KY", + "Clark__KY", + "Laurel__KY", + "Clay__KY", + "Jackson__KY", + "Wayne__KY", + "Morgan__KY", + "Estill__KY", + "Fleming__KY", + "Mason__KY", + "Floyd__KY", + "Pike__KY", + "Knott__KY", + "Johnson__KY", + "Franklin__KY", + "Rockcastle__KY", + "Garrard__KY", + "Scioto__OH", + "Shelby__KY", + "Magoffin__KY", + "Perry__KY", + "Knox__KY", + "Larue__KY", + "Leslie__KY", + "Letcher__KY", + "Pulaski__KY", + "Marion__KY", + "Washington__KY", + "Martin__KY", + "Mingo__WV", + "Powell__KY", + "Owen__KY", + "Barbour__WV", + "Taylor__WV", + "Harrison__WV", + "Upshur__WV", + "Tucker__WV", + "Boone__WV", + "Lincoln__WV", + "Kanawha__WV", + "Braxton__WV", + "Clay__WV", + "Gilmer__WV", + "Lewis__WV", + "Jefferson__OH", + "Brooke__WV", + "Cabell__WV", + "Putnam__WV", + "Mason__WV", + "Gallia__OH", + "Calhoun__WV", + "Wirt__WV", + "Ritchie__WV", + "Nicholas__WV", + "Roane__WV", + "Doddridge__WV", + "Fayette__WV", + "Summers__WV", + "Raleigh__WV", + "Greenbrier__WV", + "Grant__WV", + "Pocahontas__WV", + "Monroe__WV", + "Hardy__WV", + "Marion__WV", + "Jackson__WV", + "Logan__WV", + "Wyoming__WV", + "Monongalia__WV", + "Belmont__OH", + "Marshall__WV", + "Wetzel__WV", + "Meigs__OH", + "McDowell__WV", + "Webster__WV", + "Pendleton__WV", + "Washington__OH", + "Pleasants__WV", + "Wood__WV", + "Randolph__WV", + "Tyler__WV", + "Monroe__OH", + "Adams__OH", + "Highland__OH", + "Vinton__OH", + "Athens__OH", + "Hocking__OH", + "Shelby__OH", + "Logan__OH", + "Auglaize__OH", + "Harrison__OH", + "Warren__OH", + "Brown__OH", + "Clinton__OH", + "Butler__OH", + "Montgomery__OH", + "Carroll__OH", + "Champaign__OH", + "Madison__OH", + "Clark__OH", + "Miami__OH", + "Greene__OH", + "Fayette__OH", + "Tuscarawas__OH", + "Coshocton__OH", + "Muskingum__OH", + "Licking__OH", + "Holmes__OH", + "Guernsey__OH", + "Marion__OH", + "Darke__OH", + "Preble__OH", + "Jay__IN", + "Morrow__OH", + "Knox__OH", + "Delaware__OH", + "Franklin__OH", + "Union__OH", + "Fairfield__OH", + "Pickaway__OH", + "Perry__OH", + "Ross__OH", + "Jackson__OH", + "Noble__OH", + "Hardin__OH", + "Pike__OH", + "Richland__OH", + "Mercer__OH", + "Morgan__OH", + "Stark__OH", + "Allen__OH", + "Hancock__OH", + "Putnam__OH", + "Van Wert__OH", + "Ashland__OH", + "Huron__OH", + "Wayne__OH", + "Lake__OH", + "Geauga__OH", + "Seneca__OH", + "Crawford__OH", + "Wyandot__OH", + "Cuyahoga__OH", + "Summit__OH", + "Medina__OH", + "Lorain__OH", + "Paulding__OH", + "Williams__OH", + "Defiance__OH", + "DeKalb__IN", + "Henry__OH", + "Erie__OH", + "Fulton__OH", + "Lucas__OH", + "Portage__OH", + "Wood__OH", + "Ottawa__OH", + "Sandusky__OH", + "Van Buren__MI", + "Berrien__MI", + "Cass__MI", + "Adams__IN", + "Wells__IN", + "Allen__IN", + "Noble__IN", + "Whitley__IN", + "Huntington__IN", + "Blackford__IN", + "Grant__IN", + "Cook__IL", + "Will__IL", + "Boone__IL", + "McHenry__IL", + "Winnebago__IL", + "Whiteside__IL", + "Stephenson__IL", + "Lake__IL", + "DuPage__IL", + "Kane__IL", + "DeKalb__IL", + "Lee__IL", + "Ogle__IL", + "Grundy__IL", + "Kankakee__IL", + "Livingston__IL", + "Alexandria__VA", + "Bristol__VA", + "Buena Vista__VA", + "Chesapeake__VA", + "Colonial Heights__VA", + "Danville__VA", + "Galax__VA", + "Hampton__VA", + "Harrisonburg__VA", + "Hopewell__VA", + "Lynchburg__VA", + "Manassas Park__VA", + "Newport News__VA", + "Norfolk__VA", + "Petersburg__VA", + "Poquoson__VA", + "Portsmouth__VA", + "Salem__VA", + "Staunton__VA", + "Suffolk__VA", + "Virginia Beach__VA", + "Waynesboro__VA", + "Williamsburg__VA", + "Charlottesville__VA", + "Covington__VA", + "Emporia__VA", + "Falls Church__VA", + "Fredericksburg__VA", + "Lexington__VA", + "Manassas__VA", + "Martinsville__VA", + "Norton__VA", + "Radford__VA", + "Winchester__VA" + ], + "TVA_LGEE": [ + "Sullivan__TN", + "Lee__VA", + "Bell__KY", + "Avery__NC", + "Cherokee__NC", + "Clay__NC", + "Gordon__GA", + "Walker__GA", + "Whitfield__GA", + "Catoosa__GA", + "Chattooga__GA", + "Union__GA", + "Fannin__GA", + "Cherokee__AL", + "Murray__GA", + "Towns__GA", + "Marshall__AL", + "Cullman__AL", + "DeKalb__AL", + "Colbert__AL", + "Tishomingo__MS", + "Lauderdale__AL", + "Franklin__AL", + "Lawrence__AL", + "Morgan__AL", + "Jackson__AL", + "Marion__TN", + "Franklin__TN", + "Limestone__AL", + "Lawrence__TN", + "Madison__AL", + "Lincoln__TN", + "Alcorn__MS", + "McNairy__TN", + "Prentiss__MS", + "Tippah__MS", + "Leake__MS", + "Attala__MS", + "Benton__MS", + "Marshall__MS", + "Union__MS", + "Calhoun__MS", + "Webster__MS", + "Pontotoc__MS", + "Yalobusha__MS", + "Lafayette__MS", + "Chickasaw__MS", + "Clay__MS", + "Choctaw__MS", + "Monroe__MS", + "Tallahatchie__MS", + "Tate__MS", + "Shelby__TN", + "Rankin__MS", + "Itawamba__MS", + "Lee__MS", + "Newton__MS", + "Kemper__MS", + "Neshoba__MS", + "Panola__MS", + "Lowndes__MS", + "Oktibbeha__MS", + "Scott__MS", + "Noxubee__MS", + "Hardin__TN", + "Winston__MS", + "Anderson__TN", + "Knox__TN", + "Morgan__TN", + "Bedford__TN", + "Marshall__TN", + "Williamson__TN", + "Coffee__TN", + "Moore__TN", + "Benton__TN", + "Carroll__TN", + "Cumberland__TN", + "Rhea__TN", + "Sequatchie__TN", + "Bledsoe__TN", + "Hamilton__TN", + "Monroe__TN", + "Blount__TN", + "Sevier__TN", + "Bradley__TN", + "Polk__TN", + "Campbell__TN", + "Claiborne__TN", + "Warren__TN", + "Rutherford__TN", + "DeKalb__TN", + "Cannon__TN", + "Madison__TN", + "Gibson__TN", + "Henry__TN", + "Carter__TN", + "Unicoi__TN", + "Washington__TN", + "Cheatham__TN", + "Robertson__TN", + "Dickson__TN", + "Montgomery__TN", + "Davidson__TN", + "Henderson__TN", + "Chester__TN", + "Hancock__TN", + "Clay__TN", + "Jackson__TN", + "Cocke__TN", + "Greene__TN", + "Crockett__TN", + "Haywood__TN", + "Putnam__TN", + "Roane__TN", + "White__TN", + "Wilson__TN", + "Decatur__TN", + "Hickman__TN", + "Dyer__TN", + "Lake__TN", + "Fayette__TN", + "Hardeman__TN", + "Pickett__TN", + "Fentress__TN", + "Grundy__TN", + "Obion__TN", + "Giles__TN", + "Maury__TN", + "Lewis__TN", + "Grainger__TN", + "Hawkins__TN", + "Hamblen__TN", + "Jefferson__TN", + "Lauderdale__TN", + "Humphreys__TN", + "Houston__TN", + "Smith__TN", + "Johnson__TN", + "Union__TN", + "Loudon__TN", + "Tipton__TN", + "Wayne__TN", + "Sumner__TN", + "Trousdale__TN", + "Macon__TN", + "McMinn__TN", + "Meigs__TN", + "Stewart__TN", + "Overton__TN", + "Perry__TN", + "Scott__TN", + "Weakley__TN", + "Allen__KY", + "Warren__KY", + "Simpson__KY", + "Edmonson__KY", + "Fayette__KY", + "Grayson__KY", + "Jefferson__KY", + "Ohio__KY", + "Todd__KY", + "Logan__KY", + "Butler__KY", + "Christian__KY", + "Caldwell__KY", + "Lyon__KY", + "Calloway__KY", + "Marshall__KY", + "Carlisle__KY", + "Carroll__KY", + "Trigg__KY", + "Cumberland__KY", + "Monroe__KY", + "Woodford__KY", + "Fulton__KY", + "Hickman__KY", + "Graves__KY", + "Harlan__KY", + "Oldham__KY", + "Whitley__KY", + "Muhlenberg__KY", + "Van Buren__TN" + ], + "Carolina": [ + "Rockingham__NC", + "Caswell__NC", + "Alleghany__NC", + "Granville__NC", + "Alamance__NC", + "Guilford__NC", + "Orange__NC", + "Randolph__NC", + "Chatham__NC", + "Iredell__NC", + "Anson__NC", + "Beaufort__NC", + "Pitt__NC", + "Craven__NC", + "Bladen__NC", + "Columbus__NC", + "Cumberland__NC", + "Sampson__NC", + "Brunswick__NC", + "Horry__SC", + "Mecklenburg__NC", + "Cabarrus__NC", + "Lincoln__NC", + "Rowan__NC", + "Stanly__NC", + "Carteret__NC", + "Person__NC", + "Catawba__NC", + "Wake__NC", + "Durham__NC", + "Lee__NC", + "Pamlico__NC", + "Jones__NC", + "Harnett__NC", + "Johnston__NC", + "Robeson__NC", + "Davie__NC", + "Forsyth__NC", + "Davidson__NC", + "Yadkin__NC", + "Duplin__NC", + "Wayne__NC", + "Onslow__NC", + "Lenoir__NC", + "Edgecombe__NC", + "Nash__NC", + "Stokes__NC", + "Franklin__NC", + "Vance__NC", + "Warren__NC", + "Greene__NC", + "Halifax__NC", + "Moore__NC", + "Hoke__NC", + "Wilkes__NC", + "Wilson__NC", + "Gaston__NC", + "York__SC", + "Union__NC", + "Montgomery__NC", + "New Hanover__NC", + "Pender__NC", + "Richmond__NC", + "Scotland__NC", + "Marlboro__SC", + "Surry__NC", + "Caldwell__NC", + "Alexander__NC", + "Watauga__NC", + "Ashe__NC", + "McDowell__NC", + "Mitchell__NC", + "Buncombe__NC", + "Transylvania__NC", + "Henderson__NC", + "Madison__NC", + "Burke__NC", + "Cleveland__NC", + "Rutherford__NC", + "Cherokee__SC", + "Graham__NC", + "Haywood__NC", + "Swain__NC", + "Jackson__NC", + "Macon__NC", + "Polk__NC", + "Yancey__NC", + "Abbeville__SC", + "Anderson__SC", + "Greenville__SC", + "McCormick__SC", + "Greenwood__SC", + "Aiken__SC", + "Lexington__SC", + "Saluda__SC", + "Edgefield__SC", + "Barnwell__SC", + "Allendale__SC", + "Pickens__SC", + "Bamberg__SC", + "Orangeburg__SC", + "Colleton__SC", + "Beaufort__SC", + "Jasper__SC", + "Berkeley__SC", + "Charleston__SC", + "Dorchester__SC", + "Williamsburg__SC", + "Calhoun__SC", + "Spartanburg__SC", + "Union__SC", + "Chester__SC", + "Fairfield__SC", + "Chesterfield__SC", + "Darlington__SC", + "Florence__SC", + "Clarendon__SC", + "Marion__SC", + "Lee__SC", + "Dillon__SC", + "Kershaw__SC", + "Georgetown__SC", + "Laurens__SC", + "Hampton__SC", + "Richland__SC", + "Lancaster__SC", + "Sumter__SC", + "Newberry__SC", + "Oconee__SC", + "Rabun__GA" + ], + "SOCO": [ + "Banks__GA", + "Habersham__GA", + "Franklin__GA", + "Jackson__GA", + "Hall__GA", + "Stephens__GA", + "Barrow__GA", + "Oconee__GA", + "Cobb__GA", + "Cherokee__GA", + "Paulding__GA", + "Bartow__GA", + "Floyd__GA", + "Richmond__GA", + "Butts__GA", + "Monroe__GA", + "Henry__GA", + "Carroll__GA", + "Haralson__GA", + "Fulton__GA", + "Pickens__GA", + "Forsyth__GA", + "Dawson__GA", + "Clarke__GA", + "Oglethorpe__GA", + "Madison__GA", + "Clayton__GA", + "DeKalb__GA", + "Fayette__GA", + "Columbia__GA", + "Coweta__GA", + "Dade__GA", + "Lumpkin__GA", + "Gilmer__GA", + "Rockdale__GA", + "Gwinnett__GA", + "Douglas__GA", + "Elbert__GA", + "Hart__GA", + "Polk__GA", + "Warren__GA", + "Greene__GA", + "Morgan__GA", + "Walton__GA", + "White__GA", + "Newton__GA", + "Jasper__GA", + "Lincoln__GA", + "McDuffie__GA", + "Putnam__GA", + "Spalding__GA", + "Wilkes__GA", + "Appling__GA", + "Jeff Davis__GA", + "Wayne__GA", + "Ware__GA", + "Lanier__GA", + "Atkinson__GA", + "Bacon__GA", + "Coffee__GA", + "Dougherty__GA", + "Calhoun__GA", + "Miller__GA", + "Wilkinson__GA", + "Jones__GA", + "Baldwin__GA", + "Washington__GA", + "Hancock__GA", + "Ben Hill__GA", + "Wilcox__GA", + "Berrien__GA", + "Cook__GA", + "Tift__GA", + "Bibb__GA", + "Peach__GA", + "Laurens__GA", + "Bleckley__GA", + "Dodge__GA", + "Brantley__GA", + "Glynn__GA", + "Pierce__GA", + "Thomas__GA", + "Brooks__GA", + "Lowndes__GA", + "Bryan__GA", + "Bulloch__GA", + "Evans__GA", + "Emanuel__GA", + "Burke__GA", + "Jefferson__GA", + "Jenkins__GA", + "Terrell__GA", + "Charlton__GA", + "Camden__GA", + "Candler__GA", + "Echols__GA", + "Chatham__GA", + "Effingham__GA", + "Chattahoochee__GA", + "Clay__GA", + "Quitman__GA", + "Clinch__GA", + "Colquitt__GA", + "Troup__GA", + "Meriwether__GA", + "Crawford__GA", + "Crisp__GA", + "Dooly__GA", + "Decatur__GA", + "Mitchell__GA", + "Telfair__GA", + "Macon__GA", + "Houston__GA", + "Worth__GA", + "Lee__GA", + "Early__GA", + "Seminole__GA", + "Johnson__GA", + "Toombs__GA", + "Treutlen__GA", + "Montgomery__GA", + "Long__GA", + "Tattnall__GA", + "McIntosh__GA", + "Grady__GA", + "Harris__GA", + "Muscogee__GA", + "Talbot__GA", + "Heard__GA", + "Twiggs__GA", + "Pulaski__GA", + "Irwin__GA", + "Lamar__GA", + "Pike__GA", + "Wheeler__GA", + "Liberty__GA", + "Schley__GA", + "Taylor__GA", + "Marion__GA", + "Russell__AL", + "Randolph__GA", + "Screven__GA", + "Stewart__GA", + "Sumter__GA", + "Turner__GA", + "Upson__GA", + "Webster__GA", + "Bay__FL", + "Washington__FL", + "Gulf__FL", + "Calhoun__FL", + "Jackson__FL", + "Escambia__FL", + "Santa Rosa__FL", + "Holmes__FL", + "Okaloosa__FL", + "Walton__FL", + "Bibb__AL", + "Tuscaloosa__AL", + "Chilton__AL", + "Jefferson__AL", + "Shelby__AL", + "Etowah__AL", + "Blount__AL", + "Walker__AL", + "St. Clair__AL", + "Talladega__AL", + "Calhoun__AL", + "Cleburne__AL", + "Chambers__AL", + "Lee__AL", + "Randolph__AL", + "Clay__AL", + "Choctaw__AL", + "Tallapoosa__AL", + "Coosa__AL", + "Winston__AL", + "Fayette__AL", + "Marion__AL", + "Pickens__AL", + "Greene__AL", + "Hale__AL", + "Lamar__AL", + "Sumter__AL", + "Perry__AL", + "Mobile__AL", + "Clarke__MS", + "Lauderdale__MS", + "Baker__GA", + "Glascock__GA", + "Taliaferro__GA" + ], + "Florida": [ + "Baker__FL", + "Leon__FL", + "Liberty__FL", + "Franklin__FL", + "Wakulla__FL", + "Gadsden__FL", + "Madison__FL", + "Jefferson__FL", + "Taylor__FL", + "Alachua__FL", + "Putnam__FL", + "Gilchrist__FL", + "Clay__FL", + "Levy__FL", + "Duval__FL", + "Union__FL", + "Bradford__FL", + "Brevard__FL", + "Orange__FL", + "Citrus__FL", + "Marion__FL", + "Hernando__FL", + "Columbia__FL", + "Hamilton__FL", + "Suwannee__FL", + "Lafayette__FL", + "Dixie__FL", + "Nassau__FL", + "St. Johns__FL", + "Flagler__FL", + "Volusia__FL", + "Pasco__FL", + "Lake__FL", + "Polk__FL", + "Sumter__FL", + "Osceola__FL", + "Seminole__FL", + "Pinellas__FL", + "Hillsborough__FL", + "Indian River__FL", + "Palm Beach__FL", + "Broward__FL", + "Miami-Dade__FL", + "Charlotte__FL", + "Lee__FL", + "Hendry__FL", + "Collier__FL", + "DeSoto__FL", + "Glades__FL", + "Okeechobee__FL", + "Hardee__FL", + "Highlands__FL", + "Manatee__FL", + "Sarasota__FL", + "Martin__FL", + "St. Lucie__FL", + "Monroe__FL" + ], + "AEC": [ + "Baldwin__AL", + "Houston__AL", + "Elmore__AL", + "Autauga__AL", + "Montgomery__AL", + "Dallas__AL", + "Escambia__AL", + "Monroe__AL", + "Dale__AL", + "Barbour__AL", + "Pike__AL", + "Bullock__AL", + "Butler__AL", + "Washington__AL", + "Clarke__AL", + "Wilcox__AL", + "Marengo__AL", + "Crenshaw__AL", + "Geneva__AL", + "Coffee__AL", + "Covington__AL", + "Conecuh__AL", + "Henry__AL", + "Macon__AL", + "Lowndes__AL" + ], + "LRZ8_9_10": [ + "Jackson__MS", + "Adams__MS", + "Franklin__MS", + "Wilkinson__MS", + "Amite__MS", + "Pike__MS", + "Lincoln__MS", + "Carroll__MS", + "Bolivar__MS", + "Coahoma__MS", + "Sunflower__MS", + "Washington__MS", + "Chicot__AR", + "Leflore__MS", + "Grenada__MS", + "Holmes__MS", + "Montgomery__MS", + "Jefferson__MS", + "Claiborne__MS", + "Hinds__MS", + "Jasper__MS", + "Wayne__MS", + "Copiah__MS", + "Covington__MS", + "Forrest__MS", + "Lamar__MS", + "Jones__MS", + "Jefferson Davis__MS", + "Smith__MS", + "DeSoto__MS", + "Perry__MS", + "Stone__MS", + "George__MS", + "Greene__MS", + "Hancock__MS", + "Pearl River__MS", + "Harrison__MS", + "Madison__MS", + "Humphreys__MS", + "Yazoo__MS", + "Issaquena__MS", + "Warren__MS", + "Marion__MS", + "Lawrence__MS", + "Walthall__MS", + "Quitman__MS", + "Simpson__MS", + "Sharkey__MS", + "Tunica__MS", + "Crittenden__AR", + "Clay__AR", + "Boone__AR", + "Arkansas__AR", + "Ashley__AR", + "Baxter__AR", + "Izard__AR", + "Marion__AR", + "Bradley__AR", + "Ouachita__AR", + "Dallas__AR", + "Calhoun__AR", + "Desha__AR", + "Hot Spring__AR", + "Clark__AR", + "Cleburne__AR", + "Van Buren__AR", + "Independence__AR", + "White__AR", + "Stone__AR", + "Cleveland__AR", + "Jefferson__AR", + "Lincoln__AR", + "Columbia__AR", + "Lafayette__AR", + "Pope__AR", + "Faulkner__AR", + "Conway__AR", + "Craighead__AR", + "Greene__AR", + "Mississippi__AR", + "Poinsett__AR", + "St. Francis__AR", + "Cross__AR", + "Drew__AR", + "Pulaski__AR", + "Lonoke__AR", + "Perry__AR", + "Fulton__AR", + "Sharp__AR", + "Garland__AR", + "Saline__AR", + "Grant__AR", + "Nevada__AR", + "Hempstead__AR", + "Montgomery__AR", + "Pike__AR", + "Jackson__AR", + "Woodruff__AR", + "Lawrence__AR", + "Randolph__AR", + "Lee__AR", + "Phillips__AR", + "Yell__AR", + "Prairie__AR", + "Searcy__AR", + "Monroe__AR", + "Union__AR", + "Scott__AR", + "Union__LA", + "Acadia__LA", + "St. Landry__LA", + "Lafayette__LA", + "Jefferson Davis__LA", + "Vermilion__LA", + "Allen__LA", + "Evangeline__LA", + "Vernon__LA", + "Ascension__LA", + "Livingston__LA", + "East Baton Rouge__LA", + "Assumption__LA", + "St. Mary__LA", + "St. Martin__LA", + "St. James__LA", + "Lafourche__LA", + "Avoyelles__LA", + "Rapides__LA", + "Concordia__LA", + "Calcasieu__LA", + "Beauregard__LA", + "Claiborne__LA", + "Lincoln__LA", + "Bienville__LA", + "Jackson__LA", + "Webster__LA", + "Natchitoches__LA", + "Bossier__LA", + "Cameron__LA", + "Caldwell__LA", + "LaSalle__LA", + "Catahoula__LA", + "West Baton Rouge__LA", + "Iberville__LA", + "East Feliciana__LA", + "West Feliciana__LA", + "East Carroll__LA", + "Madison__LA", + "Franklin__LA", + "Grant__LA", + "Winn__LA", + "Iberia__LA", + "Pointe Coupee__LA", + "Jefferson__LA", + "Plaquemines__LA", + "Orleans__LA", + "St. Charles__LA", + 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Willow__NE", + "Furnas__NE", + "Harlan__NE", + "Gage__NE", + "Jefferson__NE", + "Garden__NE", + "Garfield__NE", + "Greeley__NE", + "Wheeler__NE", + "Merrick__NE", + "York__NE", + "Hitchcock__NE", + "Hayes__NE", + "Howard__NE", + "Nance__NE", + "Kearney__NE", + "Keith__NE", + "Keya Paha__NE", + "Loup__NE", + "McPherson__NE", + "Pawnee__NE", + "Perkins__NE", + "Rock__NE", + "Seward__NE", + "Valley__NE", + "Deuel__NE" + ], + "CSWS": [ + "Butler__MO", + "Ripley__MO", + "Howell__MO", + "Carroll__AR", + "Benton__AR", + "Washington__AR", + "Madison__AR", + "Newton__AR", + "Crawford__AR", + "Sebastian__AR", + "Franklin__AR", + "Logan__AR", + "Howard__AR", + "Sevier__AR", + "Polk__AR", + "Johnson__AR", + "Little River__AR", + "Miller__AR", + "Le Flore__OK", + "Caddo__LA", + "De Soto__LA", + "Red River__TX", + "Bowie__TX", + "Cass__TX", + "Camp__TX", + "Morris__TX", + "Marion__TX", + "Upshur__TX", + "Smith__TX", + "Gregg__TX", + "Harrison__TX", + "Panola__TX", + "Shelby__TX", + "Wood__TX", + "Sequoyah__OK", + "Adair__OK", + "Atoka__OK", + "Choctaw__OK", + "Pittsburg__OK", + "Beckham__OK", + "Washita__OK", + "Roger Mills__OK", + "Caddo__OK", + "Bryan__OK", + "Fannin__TX", + "Kiowa__OK", + "Pushmataha__OK", + "McCurtain__OK", + "Coal__OK", + "Comanche__OK", + "Cotton__OK", + "Rogers__OK", + "Nowata__OK", + "Tulsa__OK", + "Greer__OK", + "Jackson__OK", + "Harmon__OK", + "Haskell__OK", + "Hughes__OK", + "Montague__TX", + "Latimer__OK", + "McIntosh__OK", + "Washington__OK", + "Tillman__OK", + "Wagoner__OK" + ], + "MPS": [ + "Gentry__MO", + "Buchanan__MO", + "Andrew__MO", + "Atchison__MO", + "Barton__MO", + "Vernon__MO", + "Bates__MO", + "Pettis__MO", + "Johnson__MO", + "Jackson__MO", + "Clay__MO", + "Platte__MO", + "Nodaway__MO", + "Worth__MO", + "Holt__MO", + "Lafayette__MO" + ], + "EDE": [ + "Barry__MO", + "Stone__MO", + "Lawrence__MO", + "McDonald__MO", + "Dade__MO", + "Jasper__MO", + "Hickory__MO", + "Cedar__MO", + "Polk__MO", + "Christian__MO", + "Taney__MO", + "Dallas__MO", + "Newton__MO", + "Cherokee__KS" + ], + "WR": [ + "Doniphan__KS", + "Wilson__KS", + "Neosho__KS", + "Anderson__KS", + "Allen__KS", + "Bourbon__KS", + "Atchison__KS", + "Jackson__KS", + "Brown__KS", + "Jefferson__KS", + "Nemaha__KS", + "Butler__KS", + "Cowley__KS", + "Marion__KS", + "Harvey__KS", + "Chase__KS", + "Morris__KS", + "Lyon__KS", + "Chautauqua__KS", + "Elk__KS", + "Crawford__KS", + "Labette__KS", + "Dickinson__KS", + "Coffey__KS", + "Woodson__KS", + "Sumner__KS", + "Saline__KS", + "Geary__KS", + "Douglas__KS", + "Shawnee__KS", + "Osage__KS", + "Greenwood__KS", + "McPherson__KS", + "Wabaunsee__KS", + "Reno__KS", + "Sedgwick__KS", + "Pottawatomie__KS", + "Montgomery__KS", + "Linn__KS", + "Marshall__KS" + ], + "SPRM": ["Greene__MO"], + "KACY": ["Wyandotte__KS"], + "GRDA": ["Ottawa__OK", "Delaware__OK", "Cherokee__OK", "Mayes__OK", "Craig__OK"], + "SPS": [ + "Parmer__TX", + "Cochran__TX", + "Bailey__TX", + "Dallam__TX", + "Hartley__TX", + "Donley__TX", + "Gray__TX", + "Gaines__TX", + "Yoakum__TX", + "Hale__TX", + "Lamb__TX", + "Hansford__TX", + "Hemphill__TX", + "Hockley__TX", + "Lubbock__TX", + "Terry__TX", + "Hutchinson__TX", + "Lipscomb__TX", + "Lynn__TX", + "Sherman__TX", + "Moore__TX", + "Potter__TX", + "Randall__TX", + "Curry__NM", + "Lea__NM", + "Quay__NM", + "Roosevelt__NM", + "Union__NM", + "Beaver__OK", + "Texas__OK", + "Cimarron__OK" + ], + "WFEC": [ + "Alfalfa__OK", + "Woods__OK", + "Harper__OK", + "Dewey__OK", + "Blaine__OK", + "Custer__OK", + "Grady__OK", + "Jefferson__OK", + "Love__OK", + "Stephens__OK", + "Woodward__OK", + "Ellis__OK" + ], + "OKGE": [ + "Johnston__OK", + "Major__OK", + "Canadian__OK", + "McClain__OK", + "Oklahoma__OK", + "Carter__OK", + "Muskogee__OK", + "Cleveland__OK", + "Lincoln__OK", + "Pottawatomie__OK", + "Pontotoc__OK", + "Creek__OK", + "Okmulgee__OK", + "Osage__OK", + "Payne__OK", + "Garfield__OK", + "Logan__OK", + "Murray__OK", + "Garvin__OK", + "Grant__OK", + "Okfuskee__OK", + "Seminole__OK", + "Kay__OK", + "Kingfisher__OK", + "Marshall__OK", + "Pawnee__OK", + "Noble__OK" + ], + "SECI": [ + "Stevens__KS", + "Barber__KS", + "Barton__KS", + "Stafford__KS", + "Ellsworth__KS", + "Russell__KS", + "Cheyenne__KS", + "Sherman__KS", + "Clark__KS", + "Ford__KS", + "Comanche__KS", + "Clay__KS", + "Cloud__KS", + "Mitchell__KS", + "Rawlins__KS", + "Decatur__KS", + "Ottawa__KS", + "Kiowa__KS", + "Edwards__KS", + "Trego__KS", + "Ellis__KS", + "Rush__KS", + "Rooks__KS", + "Rice__KS", + "Finney__KS", + "Gray__KS", + "Kearny__KS", + "Scott__KS", + "Meade__KS", + "Riley__KS", + "Lane__KS", + "Gove__KS", + "Logan__KS", + "Ness__KS", + "Graham__KS", + "Norton__KS", + "Phillips__KS", + "Stanton__KS", + "Grant__KS", + "Greeley__KS", + "Hamilton__KS", + "Harper__KS", + "Haskell__KS", + "Hodgeman__KS", + "Republic__KS", + "Jewell__KS", + "Kingman__KS", + "Lincoln__KS", + "Wichita__KS", + "Wallace__KS", + "Osborne__KS", + "Morton__KS", + "Pawnee__KS", + "Pratt__KS", + "Thomas__KS", + "Seward__KS", + "Sheridan__KS", + "Smith__KS", + "Washington__KS" + ], + "LES": ["Lancaster__NE"], + "AVA": [ + "Ferry__WA", + "Stevens__WA", + "Pend Oreille__WA", + "Lincoln__WA", + "Spokane__WA", + "Whitman__WA", + "Bonner__ID", + "Kootenai__ID", + "Benewah__ID", + "Latah__ID" + ], + "BPAT": [ + "Cowlitz__WA", + "Snohomish__WA", + "Skamania__WA", + "Mason__WA", + "San Juan__WA", + "Island__WA", + "Clark__WA", + "Pierce__WA", + "Jefferson__WA", + "Klickitat__WA", + "Kittitas__WA", + "Adams__WA", + "Kitsap__WA", + "Lewis__WA", + "Franklin__WA", + "Grays Harbor__WA", + "Columbia__WA", + "Garfield__WA", + "Clallam__WA", + "Asotin__WA", + "Walla Walla__WA", + "Benton__WA", + "Yakima__WA", + "Pacific__WA", + "Wahkiakum__WA", + "King__WA", + "Modoc__CA", + "Shoshone__ID", + "Clearwater__ID", + "Lewis__ID", + "Nez Perce__ID", + "Boundary__ID", + "Lincoln__MT", + "Flathead__MT", + "Lake__MT", + "Sanders__MT", + "Mineral__MT", + "Harney__OR", + "Baker__OR", + "Union__OR", + "Deschutes__OR", + "Wasco__OR", + "Lincoln__OR", + "Wallowa__OR", + "Crook__OR", + "Lane__OR", + "Lake__OR", + "Grant__OR", + "Wheeler__OR", + "Malheur__OR", + "Linn__OR", + "Columbia__OR", + "Jefferson__OR", + "Sherman__OR", + "Clatsop__OR", + "Gilliam__OR", + "Benton__OR", + "Umatilla__OR", + "Tillamook__OR" + ], + "IPCO": [ + "Malheur__OR", + "Canyon__ID", + "Elmore__ID", + "Twin Falls__ID", + "Custer__ID", + "Jerome__ID", + "Idaho__ID", + "Cassia__ID", + "Camas__ID", + "Minidoka__ID", + "Lemhi__ID", + "Gooding__ID", + "Lincoln__ID", + "Washington__ID", + "Owyhee__ID", + "Adams__ID", + "Valley__ID", + "Payette__ID", + "Blaine__ID", + "Ada__ID", + "Gem__ID", + "Boise__ID", + "Butte__ID" + ], + "PACW": [ + "Douglas__OR", + "Coos__OR", + "Josephine__OR", + "Jackson__OR", + "Klamath__OR", + "Curry__OR", + "Del Norte__CA", + "Siskiyou__CA" + ], + "PNM": [ + "Greenlee__AZ", + "De Baca__NM", + "Guadalupe__NM", + "Los Alamos__NM", + "Cibola__NM", + "San Juan__NM", + "Rio Arriba__NM", + "San Miguel__NM", + "Santa Fe__NM", + "Hidalgo__NM", + "Union__NM", + "Harding__NM", + "Sierra__NM", + "Taos__NM", + "Sandoval__NM", + "Luna__NM", + "Chaves__NM", + "Grant__NM", + "Catron__NM", + "McKinley__NM", + "Quay__NM", + "Bernalillo__NM", + "Torrance__NM", + "Colfax__NM", + "Lincoln__NM", + "Valencia__NM", + "Mora__NM", + "Socorro__NM", + "Lea__NM", + "Roosevelt__NM", + "Curry__NM" + ], + "PACE": [ + "San Juan__UT", + "Millard__UT", + "Box Elder__UT", + "Wasatch__UT", + "Rich__UT", + "Sanpete__UT", + "Uintah__UT", + "Juab__UT", + "Iron__UT", + "Tooele__UT", + "Carbon__UT", + "Beaver__UT", + "Morgan__UT", + "Washington__UT", + "Summit__UT", + "Weber__UT", + "Piute__UT", + "Emery__UT", + "Grand__UT", + "Garfield__UT", + "Sevier__UT", + "Utah__UT", + "Salt Lake__UT", + "Davis__UT", + "Duchesne__UT", + "Cache__UT", + "Kane__UT", + "Wayne__UT", + "Daggett__UT", + "Uinta__WY", + "Fremont__WY", + "Hot Springs__WY", + "Sweetwater__WY", + "Big Horn__WY", + "Carbon__WY", + "Washakie__WY", + "Lincoln__WY", + "Park__WY", + "Sublette__WY", + "Teton__WY", + "Franklin__ID", + "Bear Lake__ID", + "Clark__ID", + "Power__ID", + "Madison__ID", + "Bannock__ID", + "Jefferson__ID", + "Caribou__ID", + "Fremont__ID", + "Oneida__ID", + "Bonneville__ID", + "Bingham__ID", + "Teton__ID" + ], + "WACM": [ + "Goshen__WY", + "Weston__WY", + "Converse__WY", + "Johnson__WY", + "Natrona__WY", + "Crook__WY", + "Campbell__WY", + "Laramie__WY", + "Platte__WY", + "Sheridan__WY", + "Niobrara__WY", + "Albany__WY", + "Dolores__CO", + "Lake__CO", + "Ouray__CO", + "Saguache__CO", + "Rio Blanco__CO", + "Kiowa__CO", + "Yuma__CO", + "Rio Grande__CO", + "San Miguel__CO", + "Kit Carson__CO", + "Routt__CO", + "Cheyenne__CO", + "San Juan__CO", + "Logan__CO", + "Phillips__CO", + "Chaffee__CO", + "Archuleta__CO", + "Jackson__CO", + "Hinsdale__CO", + "Sedgwick__CO", + "Garfield__CO", + "Montezuma__CO", + "Delta__CO", + "Custer__CO", + "Summit__CO", + "Gunnison__CO", + "Moffat__CO", + "Montrose__CO", + "Conejos__CO", + "Grand__CO", + "Fremont__CO", + "Larimer__CO", + "Mesa__CO", + "Washington__CO", + "Mineral__CO", + "La Plata__CO", + "Pitkin__CO", + "Eagle__CO", + "Park__CO", + "Butte__SD", + "Custer__SD", + "Fall River__SD", + "Lawrence__SD", + "Meade__SD", + "Pennington__SD" + ], + "EPE": [ + "Dona Ana__NM", + "Otero__NM", + "Eddy__NM", + "El Paso__TX", + "Hudspeth__TX", + "Culberson__TX" + ], + "CISO": [ + "Butte__CA", + "Colusa__CA", + "El Dorado__CA", + "Glenn__CA", + "Humboldt__CA", + "Lake__CA", + "Lassen__CA", + "Mendocino__CA", + "Nevada__CA", + "Plumas__CA", + "Sacramento__CA", + "Shasta__CA", + "Sierra__CA", + "Sutter__CA", + "Tehama__CA", + "Trinity__CA", + "Yolo__CA", + "Yuba__CA", + "Alameda__CA", + "Contra Costa__CA", + "Marin__CA", + "Napa__CA", + "San Francisco__CA", + "San Mateo__CA", + "Santa Clara__CA", + "Santa Cruz__CA", + "Solano__CA", + "Sonoma__CA", + "Alpine__CA", + "Amador__CA", + "Calaveras__CA", + "Fresno__CA", + "Inyo__CA", + "Kings__CA", + "Madera__CA", + "Mono__CA", + "Monterey__CA", + "San Benito__CA", + "San Joaquin__CA", + "Stanislaus__CA", + "Tulare__CA", + "Tuolumne__CA", + "Orange__CA", + "San Bernardino__CA", + "San Diego__CA", + "Kern__CA", + "San Luis Obispo__CA", + "Santa Barbara__CA", + "Ventura__CA" + ], + "BANC": ["Placer__CA"], + "IID": ["Imperial__CA", "Riverside__CA"], + "LDWP": ["Los Angeles__CA"], + "TIDC": ["Mariposa__CA", "Merced__CA"], + "TEPC": ["Cochise__AZ", "Pima__AZ", "Santa Cruz__AZ"], + "GRID": ["Morrow__OR"], + "DOPD": ["Okanogan__WA", "Douglas__WA"], + "CHPD": ["Chelan__WA"], + "GCPD": ["Grant__WA"], + "PSEI": ["Whatcom__WA", "Skagit__WA"], + "Arizona": [ + "Apache__AZ", + "Coconino__AZ", + "Gila__AZ", + "Graham__AZ", + "La Paz__AZ", + "Maricopa__AZ", + "Mohave__AZ", + "Navajo__AZ", + "Pinal__AZ", + "Yavapai__AZ", + "Yuma__AZ" + ], + "PSCO": [ + "Adams__CO", + "Alamosa__CO", + "Arapahoe__CO", + "Baca__CO", + "Bent__CO", + "Boulder__CO", + "Broomfield__CO", + "Clear Creek__CO", + "Costilla__CO", + "Crowley__CO", + "Denver__CO", + "Douglas__CO", + "El Paso__CO", + "Elbert__CO", + "Gilpin__CO", + "Huerfano__CO", + "Jefferson__CO", + "Las Animas__CO", + "Lincoln__CO", + "Morgan__CO", + "Otero__CO", + "Prowers__CO", + "Pueblo__CO", + "Teller__CO", + "Weld__CO" + ], + "MT_west": [ + "Beaverhead__MT", + "Big Horn__MT", + "Blaine__MT", + "Broadwater__MT", + "Carbon__MT", + "Cascade__MT", + "Chouteau__MT", + "Deer Lodge__MT", + "Fergus__MT", + "Gallatin__MT", + "Glacier__MT", + "Golden Valley__MT", + "Granite__MT", + "Hill__MT", + "Jefferson__MT", + "Judith Basin__MT", + "Lewis and Clark__MT", + "Liberty__MT", + "Madison__MT", + "Meagher__MT", + "Missoula__MT", + "Musselshell__MT", + "Park__MT", + "Petroleum__MT", + "Pondera__MT", + "Powell__MT", + "Ravalli__MT", + "Silver Bow__MT", + "Stillwater__MT", + "Sweet Grass__MT", + "Teton__MT", + "Toole__MT", + "Treasure__MT", + "Wheatland__MT", + "Yellowstone__MT" + ], + "NEVP": [ + "Churchill__NV", + "Clark__NV", + "Douglas__NV", + "Elko__NV", + "Esmeralda__NV", + "Eureka__NV", + "Humboldt__NV", + "Lander__NV", + "Lincoln__NV", + "Lyon__NV", + "Mineral__NV", + "Nye__NV", + "Pershing__NV", + "Storey__NV", + "Washoe__NV", + "White Pine__NV", + "Carson City__NV" + ], + "PGE": [ + "Clackamas__OR", + "Hood River__OR", + "Marion__OR", + "Multnomah__OR", + "Polk__OR", + "Washington__OR", + "Yamhill__OR" + ], + "ERCOT": [ + "Anderson__TX", + "Andrews__TX", + "Angelina__TX", + "Aransas__TX", + "Archer__TX", + "Armstrong__TX", + "Atascosa__TX", + "Austin__TX", + "Bandera__TX", + "Bastrop__TX", + "Baylor__TX", + "Bee__TX", + "Bell__TX", + "Bexar__TX", + "Blanco__TX", + "Borden__TX", + "Bosque__TX", + "Brazoria__TX", + "Brazos__TX", + "Brewster__TX", + "Briscoe__TX", + "Brooks__TX", + "Brown__TX", + "Burleson__TX", + "Burnet__TX", + "Caldwell__TX", + "Calhoun__TX", + "Callahan__TX", + "Cameron__TX", + "Carson__TX", + "Castro__TX", + "Chambers__TX", + "Cherokee__TX", + "Childress__TX", + "Clay__TX", + "Coke__TX", + "Coleman__TX", + "Collin__TX", + "Collingsworth__TX", + "Colorado__TX", + "Comal__TX", + "Comanche__TX", + "Concho__TX", + "Cooke__TX", + "Coryell__TX", + "Cottle__TX", + "Crane__TX", + "Crockett__TX", + "Crosby__TX", + "Dallas__TX", + "Dawson__TX", + "DeWitt__TX", + "Deaf Smith__TX", + "Delta__TX", + "Denton__TX", + "Dickens__TX", + "Dimmit__TX", + "Duval__TX", + "Eastland__TX", + "Ector__TX", + "Edwards__TX", + "Ellis__TX", + "Erath__TX", + "Falls__TX", + "Fayette__TX", + "Fisher__TX", + "Floyd__TX", + "Foard__TX", + "Fort Bend__TX", + "Franklin__TX", + "Freestone__TX", + "Frio__TX", + "Galveston__TX", + "Garza__TX", + "Gillespie__TX", + "Glasscock__TX", + "Goliad__TX", + "Gonzales__TX", + "Grayson__TX", + "Grimes__TX", + "Guadalupe__TX", + "Hall__TX", + "Hamilton__TX", + "Hardeman__TX", + "Harris__TX", + "Haskell__TX", + "Hays__TX", + "Henderson__TX", + "Hidalgo__TX", + "Hill__TX", + "Hood__TX", + "Hopkins__TX", + "Houston__TX", + "Howard__TX", + "Hunt__TX", + "Irion__TX", + "Jack__TX", + "Jackson__TX", + "Jeff Davis__TX", + "Jim Hogg__TX", + "Jim Wells__TX", + "Johnson__TX", + "Jones__TX", + "Karnes__TX", + "Kaufman__TX", + "Kendall__TX", + "Kenedy__TX", + "Kent__TX", + "Kerr__TX", + "Kimble__TX", + "King__TX", + "Kinney__TX", + "Kleberg__TX", + "Knox__TX", + "La Salle__TX", + "Lamar__TX", + "Lampasas__TX", + "Lavaca__TX", + "Lee__TX", + "Leon__TX", + "Limestone__TX", + "Live Oak__TX", + "Llano__TX", + "Loving__TX", + "McCulloch__TX", + "McLennan__TX", + "McMullen__TX", + "Madison__TX", + "Martin__TX", + "Mason__TX", + "Matagorda__TX", + "Maverick__TX", + "Medina__TX", + "Menard__TX", + "Midland__TX", + "Milam__TX", + "Mills__TX", + "Mitchell__TX", + "Motley__TX", + "Nacogdoches__TX", + "Navarro__TX", + "Nolan__TX", + "Nueces__TX", + "Ochiltree__TX", + "Oldham__TX", + "Palo Pinto__TX", + "Parker__TX", + "Pecos__TX", + "Presidio__TX", + "Rains__TX", + "Reagan__TX", + "Real__TX", + "Reeves__TX", + "Refugio__TX", + "Roberts__TX", + "Robertson__TX", + "Rockwall__TX", + "Runnels__TX", + "Rusk__TX", + "San Patricio__TX", + "San Saba__TX", + "Schleicher__TX", + "Scurry__TX", + "Shackelford__TX", + "Somervell__TX", + "Starr__TX", + "Stephens__TX", + "Sterling__TX", + "Stonewall__TX", + "Sutton__TX", + "Swisher__TX", + "Tarrant__TX", + "Taylor__TX", + "Terrell__TX", + "Throckmorton__TX", + "Titus__TX", + "Tom Green__TX", + "Travis__TX", + "Upton__TX", + "Uvalde__TX", + "Val Verde__TX", + "Van Zandt__TX", + "Victoria__TX", + "Waller__TX", + "Ward__TX", + "Washington__TX", + "Webb__TX", + "Wharton__TX", + "Wheeler__TX", + "Wichita__TX", + "Wilbarger__TX", + "Willacy__TX", + "Williamson__TX", + "Wilson__TX", + "Winkler__TX", + "Wise__TX", + "Young__TX", + "Zapata__TX", + "Zavala__TX" + ], + "SCL_TPWR": ["Thurston__WA"] +} From bb0fa346532de5e3010d4ba8777fec574dfebc7c Mon Sep 17 00:00:00 2001 From: BainanXia Date: Fri, 2 Jul 2021 13:07:58 -0700 Subject: [PATCH 23/61] feat: add function to map buses to balancing authorities --- prereise/gather/demanddata/eia/map_ba.py | 38 ++++++++++++++++++++++++ 1 file changed, 38 insertions(+) diff --git a/prereise/gather/demanddata/eia/map_ba.py b/prereise/gather/demanddata/eia/map_ba.py index 12b81884c..60d45362e 100644 --- a/prereise/gather/demanddata/eia/map_ba.py +++ b/prereise/gather/demanddata/eia/map_ba.py @@ -1,7 +1,13 @@ +import inspect +import json +import os + import pandas as pd import requests from tqdm import tqdm +import prereise + def aggregate_ba_demand(demand, mapping): """Aggregate demand in BAs to regions as defined in the mapping dictionary @@ -95,3 +101,35 @@ def map_buses_to_county(bus_county_map): except TypeError: bus_no_county_match.append(index) return bus_county_map, bus_no_county_match + + +def map_buses_to_ba(bus_df): + """Find the Balancing Authority in the U.S. territory that each query bus belongs to + based on GIS information. + + :param (*pandas.DataFrame*) bus_df: data frame contains a list of entries with + lat and long of buses. + :return: (*tuple*) -- the first entry is the input data frame with two columns, + "County" and "BA", added for each bus and the second entry is the list of bus + indices that no BA matches. + """ + + bus_ba_map, _ = map_buses_to_county(bus_df) + + # read json file for BA_County Map + filepath = os.path.join( + os.path.dirname(inspect.getfile(prereise)), + "gather", + "data", + "BA_County_map.json", + ) + with open(filepath) as f: + ba_county_map = json.load(f) + + county_ba_map = { + value: key for key in ba_county_map for value in ba_county_map[key] + } + bus_ba_map["BA"] = bus_ba_map["County"].map(county_ba_map) + bus_no_ba_match = list(bus_ba_map.query("BA.isna()").index) + + return bus_ba_map, bus_no_ba_match From b22028cc728eead088278922786e7cb185cc4018 Mon Sep 17 00:00:00 2001 From: BainanXia Date: Fri, 2 Jul 2021 13:08:32 -0700 Subject: [PATCH 24/61] test: add tests for map_buses_to_county and map_buses_to_ba --- .../demanddata/eia/tests/test_map_ba.py | 31 +++++++++++++++++++ 1 file changed, 31 insertions(+) diff --git a/prereise/gather/demanddata/eia/tests/test_map_ba.py b/prereise/gather/demanddata/eia/tests/test_map_ba.py index 3999c9b9c..8560b27e0 100644 --- a/prereise/gather/demanddata/eia/tests/test_map_ba.py +++ b/prereise/gather/demanddata/eia/tests/test_map_ba.py @@ -1,9 +1,12 @@ +import numpy as np import pandas as pd from pandas.testing import assert_series_equal from prereise.gather.demanddata.eia.map_ba import ( aggregate_ba_demand, get_demand_in_loadzone, + map_buses_to_ba, + map_buses_to_county, ) @@ -63,3 +66,31 @@ def create_ba_to_region_dataframe(): } initial_df = pd.DataFrame.from_dict(start_data) return initial_df + + +def test_map_buses_to_county(): + bus_df = pd.DataFrame( + { + "lat": [34.0522, 29.7604, 40.7128], + "lon": [-118.2437, -95.3698, -74.0060], + }, + index=["CA", "Texas", "NY"], + ) + expected_res = ["Los Angeles__CA", "Harris__TX", "New York__NY"] + bus_county, bus_no_county_match = map_buses_to_county(bus_df) + assert bus_county["County"].tolist() == expected_res + assert bus_no_county_match == [] + + +def test_map_buses_to_ba(): + bus_df = pd.DataFrame( + { + "lat": [34.0522, 29.7604, 39.9042], + "lon": [-118.2437, -95.3698, 116.4074], + }, + index=["CA", "Texas", "Beijing"], + ) + expected_res = ["LDWP", "ERCOT", np.nan] + bus_ba, bus_no_ba_match = map_buses_to_ba(bus_df) + assert bus_ba["BA"].tolist() == expected_res + assert bus_no_ba_match == ["Beijing"] From 1a3c64454352269a0bdf89b253af5b18e8fb372d Mon Sep 17 00:00:00 2001 From: BainanXia Date: Fri, 2 Jul 2021 14:15:19 -0700 Subject: [PATCH 25/61] fix: get all data in the data folder installed with the package --- setup.py | 6 ++---- 1 file changed, 2 insertions(+), 4 deletions(-) diff --git a/setup.py b/setup.py index 79f07c74c..4be9c82ac 100644 --- a/setup.py +++ b/setup.py @@ -10,10 +10,8 @@ packages=find_packages(), package_data={ "prereise": [ - "gather/winddata/data/*.csv", - "gather/data/EIA923_Schedules_2_3_4_5_M_12_2016_Final_Revision.xlsx", - "gather/hydrodata/data/*.csv", - "gather/solardata/data/*.csv", + "gather/*/data/*", + "gather/data/*", ] }, zip_safe=False, From 4bc11654879fc2894f7cf45ee5e6c203f786b949 Mon Sep 17 00:00:00 2001 From: BainanXia Date: Fri, 2 Jul 2021 19:09:10 -0700 Subject: [PATCH 26/61] data: cache result file of running map_buses_to_ba with all buses in the US grid 118 buses failed to be matched to a BA due to mismatch county names or outside the US territory --- prereise/gather/data/all_bus_ba_map.csv | 82072 ++++++++++++++++++++++ 1 file changed, 82072 insertions(+) create mode 100644 prereise/gather/data/all_bus_ba_map.csv diff --git a/prereise/gather/data/all_bus_ba_map.csv b/prereise/gather/data/all_bus_ba_map.csv new file mode 100644 index 000000000..90d9e94fe --- /dev/null +++ b/prereise/gather/data/all_bus_ba_map.csv @@ -0,0 +1,82072 @@ +bus_id,lat,lon,County,BA +1,43.9761,-70.2211,Androscoggin__ME,ISNE 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+36373,39.1539,-84.5027,Hamilton__OH,PJM +36374,39.2661,-84.6662,Hamilton__OH,PJM +36375,39.143,-84.308,Hamilton__OH,PJM +36376,39.0171,-84.7127,Boone__KY,PJM +36377,39.0171,-84.7127,Boone__KY,PJM +36378,39.1498,-84.7222,Hamilton__OH,PJM +36379,39.2054,-84.5076,Hamilton__OH,PJM +36380,39.15,-84.5738,Hamilton__OH,PJM +36381,39.0198,-84.5071,Kenton__KY,PJM +36382,39.0198,-84.5071,Kenton__KY,PJM +36383,39.0946,-84.5729,Hamilton__OH,PJM +36384,39.0343,-84.6659,Boone__KY,PJM +36385,39.0343,-84.6659,Boone__KY,PJM +36386,39.0815,-84.6637,Boone__KY,PJM +36387,39.0815,-84.6637,Boone__KY,PJM +36388,39.0815,-84.6637,Boone__KY,PJM +36389,39.1357,-84.6705,Hamilton__OH,PJM +36390,39.1357,-84.6705,Hamilton__OH,PJM +36391,39.1357,-84.6705,Hamilton__OH,PJM +36392,39.1056,-84.5577,Hamilton__OH,PJM +36393,39.1164,-84.3747,Hamilton__OH,PJM +36394,39.1164,-84.3747,Hamilton__OH,PJM +36395,39.0144,-84.3867,Campbell__KY,PJM +36396,39.0144,-84.3867,Campbell__KY,PJM +36397,39.0511,-84.3799,Hamilton__OH,PJM +36398,39.0198,-84.4203,Campbell__KY,PJM +36399,39.2604,-84.7872,Hamilton__OH,PJM +36400,39.2604,-84.7872,Hamilton__OH,PJM +36401,39.1725,-84.713,Hamilton__OH,PJM +36402,39.3126,-84.7333,Butler__OH,PJM +36403,39.181,-84.7672,Hamilton__OH,PJM +36404,39.181,-84.7672,Hamilton__OH,PJM +36405,39.181,-84.7672,Hamilton__OH,PJM +36406,39.181,-84.7672,Hamilton__OH,PJM +36407,39.181,-84.7672,Hamilton__OH,PJM +36408,39.181,-84.7672,Hamilton__OH,PJM +36409,39.1332,-84.8098,Hamilton__OH,PJM +36410,40.5272,-83.7372,Hardin__OH,PJM +36411,40.5725,-83.3764,Marion__OH,PJM +36412,40.5364,-83.5006,Hardin__OH,PJM +36413,40.5364,-83.5006,Hardin__OH,PJM +36414,40.436,-80.9311,Jefferson__OH,PJM +36415,40.2305,-80.9873,Harrison__OH,PJM +36416,40.2986,-80.9853,Harrison__OH,PJM +36417,40.3384,-81.2935,Tuscarawas__OH,PJM +36418,40.3777,-81.3375,Tuscarawas__OH,PJM +36419,40.3777,-81.3375,Tuscarawas__OH,PJM +36420,39.1644,-83.3574,Pike__OH,PJM +36421,39.2145,-83.2154,Ross__OH,PJM +36422,39.2145,-83.2154,Ross__OH,PJM +36423,39.4186,-82.6624,Hocking__OH,PJM +36424,39.4186,-82.6624,Hocking__OH,PJM +36425,39.4543,-82.7224,Hocking__OH,PJM +36426,39.4839,-82.4495,Hocking__OH,PJM +36427,39.4839,-82.4495,Hocking__OH,PJM +36428,39.4839,-82.4495,Hocking__OH,PJM +36429,39.4656,-82.4395,Hocking__OH,PJM +36430,39.5455,-82.3277,Hocking__OH,PJM +36431,40.5253,-81.6953,Holmes__OH,PJM +36432,40.5253,-81.6953,Holmes__OH,PJM +36433,40.5657,-81.6528,Tuscarawas__OH,PJM +36434,40.5657,-81.6528,Tuscarawas__OH,PJM +36435,39.2501,-83.0497,Ross__OH,PJM +36436,39.2501,-83.0497,Ross__OH,PJM +36437,39.3426,-82.9691,Ross__OH,PJM +36438,39.2473,-82.9478,Ross__OH,PJM +36439,39.2473,-82.9478,Ross__OH,PJM +36440,39.2473,-82.9478,Ross__OH,PJM +36441,39.3355,-83.0575,Ross__OH,PJM +36442,39.3458,-83.0199,Ross__OH,PJM +36443,39.0879,-82.5998,Jackson__OH,PJM +36444,38.8791,-82.751,Jackson__OH,PJM +36445,38.8791,-82.751,Jackson__OH,PJM +36446,39.0587,-82.7515,Jackson__OH,PJM +36447,39.0298,-82.6732,Jackson__OH,PJM +36448,39.0298,-82.6732,Jackson__OH,PJM +36449,39.1591,-82.5814,Jackson__OH,PJM +36450,39.1591,-82.5814,Jackson__OH,PJM +36451,39.0941,-82.6431,Jackson__OH,PJM +36452,39.0689,-82.5004,Jackson__OH,PJM +36453,39.0689,-82.5004,Jackson__OH,PJM +36454,40.5189,-80.7831,Jefferson__OH,PJM +36455,40.4711,-80.7295,Jefferson__OH,PJM +36456,40.455,-80.6747,Jefferson__OH,PJM +36457,40.3634,-80.6987,Jefferson__OH,PJM +36458,40.3634,-80.6987,Jefferson__OH,PJM +36459,40.3942,-80.7243,Jefferson__OH,PJM +36460,40.3942,-80.7243,Jefferson__OH,PJM +36461,40.3942,-80.7243,Jefferson__OH,PJM +36462,40.3942,-80.7243,Jefferson__OH,PJM +36463,40.3942,-80.7243,Jefferson__OH,PJM +36464,40.3942,-80.7243,Jefferson__OH,PJM +36465,40.2299,-80.6856,Jefferson__OH,PJM +36466,40.3395,-80.6568,Jefferson__OH,PJM +36467,40.3395,-80.6568,Jefferson__OH,PJM +36468,40.4907,-80.6781,Jefferson__OH,PJM +36469,40.5199,-80.6237,Jefferson__OH,PJM +36470,40.5621,-82.5973,Richland__OH,PJM +36471,40.496,-82.5878,Knox__OH,PJM +36472,40.5336,-82.3453,Knox__OH,PJM +36473,40.5377,-82.1684,Holmes__OH,PJM +36474,40.5377,-82.1684,Holmes__OH,PJM +36475,40.5327,-82.5204,Knox__OH,PJM +36476,40.4622,-82.5249,Knox__OH,PJM +36477,40.3455,-82.3291,Knox__OH,PJM +36478,40.4231,-82.279,Knox__OH,PJM +36479,40.4776,-82.3428,Knox__OH,PJM +36480,40.4776,-82.3428,Knox__OH,PJM +36481,40.4278,-82.478,Knox__OH,PJM +36482,40.4938,-82.4714,Knox__OH,PJM +36483,40.2617,-82.4773,Licking__OH,PJM +36484,40.3544,-82.5128,Knox__OH,PJM +36485,40.3544,-82.5128,Knox__OH,PJM +36486,38.4649,-82.4647,Lawrence__OH,PJM +36487,38.5251,-82.5376,Lawrence__OH,PJM +36488,38.5251,-82.5376,Lawrence__OH,PJM +36489,38.568,-82.3653,Lawrence__OH,PJM +36490,38.4943,-82.7391,Greenup__KY,PJM +36491,38.6157,-82.7123,Lawrence__OH,PJM +36492,38.6157,-82.7123,Lawrence__OH,PJM +36493,38.5866,-82.7494,Lawrence__OH,PJM +36494,38.5866,-82.7494,Lawrence__OH,PJM +36495,38.5228,-82.652,Lawrence__OH,PJM +36496,38.5228,-82.652,Lawrence__OH,PJM +36497,38.5228,-82.652,Lawrence__OH,PJM +36498,38.4835,-82.3124,Lawrence__OH,PJM +36499,38.4835,-82.3124,Lawrence__OH,PJM +36500,38.4751,-82.3505,Lawrence__OH,PJM +36501,38.4751,-82.3505,Lawrence__OH,PJM +36502,38.4751,-82.3505,Lawrence__OH,PJM +36503,38.4751,-82.3505,Lawrence__OH,PJM +36504,38.4751,-82.3505,Lawrence__OH,PJM +36505,38.4751,-82.3505,Lawrence__OH,PJM +36506,38.4751,-82.3505,Lawrence__OH,PJM +36507,38.4438,-82.5289,Lawrence__OH,PJM +36508,38.505,-82.618,Lawrence__OH,PJM +36509,38.505,-82.618,Lawrence__OH,PJM +36510,38.466,-82.6923,Boyd__KY,PJM +36511,39.904,-82.2605,Perry__OH,PJM +36512,39.904,-82.2605,Perry__OH,PJM +36513,40.0771,-82.5493,Licking__OH,PJM +36514,40.1236,-82.5239,Licking__OH,PJM +36515,40.0054,-82.2984,Licking__OH,PJM +36516,39.9783,-82.3775,Licking__OH,PJM +36517,40.0588,-82.2165,Licking__OH,PJM +36518,39.95,-82.3421,Licking__OH,PJM +36519,39.9805,-82.5547,Licking__OH,PJM +36520,39.9805,-82.5547,Licking__OH,PJM +36521,39.9839,-82.4776,Licking__OH,PJM +36522,40.0373,-82.0875,Muskingum__OH,PJM +36523,40.0989,-82.1174,Muskingum__OH,PJM +36524,40.112,-82.4501,Licking__OH,PJM +36525,40.1534,-82.4,Licking__OH,PJM +36526,40.1534,-82.4,Licking__OH,PJM +36527,40.1534,-82.4,Licking__OH,PJM +36528,40.1534,-82.4,Licking__OH,PJM +36529,40.1534,-82.4,Licking__OH,PJM +36530,40.1534,-82.4,Licking__OH,PJM +36531,40.1534,-82.4,Licking__OH,PJM +36532,40.0831,-82.2603,Licking__OH,PJM +36533,40.0831,-82.2603,Licking__OH,PJM +36534,40.0831,-82.2603,Licking__OH,PJM +36535,40.0831,-82.2603,Licking__OH,PJM +36536,40.0831,-82.2603,Licking__OH,PJM +36537,40.0831,-82.2603,Licking__OH,PJM +36538,40.0831,-82.2603,Licking__OH,PJM +36539,40.1349,-82.3455,Licking__OH,PJM +36540,40.1425,-82.4128,Licking__OH,PJM +36541,40.1425,-82.4128,Licking__OH,PJM +36542,40.3337,-83.806,Logan__OH,PJM +36543,40.3337,-83.806,Logan__OH,PJM +36544,40.3337,-83.806,Logan__OH,PJM +36545,40.3081,-83.8057,Logan__OH,PJM +36546,40.3282,-83.7382,Logan__OH,PJM +36547,40.3366,-83.6331,Logan__OH,PJM +36548,40.3366,-83.6331,Logan__OH,PJM +36549,40.4172,-83.8189,Logan__OH,PJM +36550,40.3932,-83.5773,Logan__OH,PJM +36551,40.0698,-83.3379,Madison__OH,PJM +36552,39.9697,-83.2976,Madison__OH,PJM +36553,40.5038,-82.8673,Morrow__OH,PJM +36554,40.518,-82.8081,Morrow__OH,PJM +36555,40.518,-82.8081,Morrow__OH,PJM +36556,40.4352,-82.8284,Morrow__OH,PJM +36557,38.9615,-82.0975,Meigs__OH,PJM +36558,39.0205,-82.2425,Meigs__OH,PJM +36559,39.1246,-82.1736,Meigs__OH,PJM +36560,39.126,-82.0013,Meigs__OH,PJM +36561,39.126,-82.0013,Meigs__OH,PJM +36562,39.0382,-82.0776,Meigs__OH,PJM +36563,39.0382,-82.0776,Meigs__OH,PJM +36564,38.8892,-81.8584,Jackson__WV,PJM +36565,38.9807,-81.9516,Mason__WV,PJM +36566,39.0765,-81.8126,Jackson__WV,PJM +36567,39.0765,-81.8126,Jackson__WV,PJM +36568,40.5125,-84.5594,Mercer__OH,PJM +36569,40.5921,-84.5756,Mercer__OH,PJM +36570,40.5921,-84.5756,Mercer__OH,PJM +36571,40.5169,-84.6126,Mercer__OH,PJM +36572,40.5179,-84.643,Mercer__OH,PJM +36573,40.4413,-84.6345,Mercer__OH,PJM +36574,40.4614,-84.7321,Mercer__OH,PJM +36575,40.4614,-84.7321,Mercer__OH,PJM +36576,40.4614,-84.7321,Mercer__OH,PJM +36577,40.4614,-84.7321,Mercer__OH,PJM +36578,40.4614,-84.7321,Mercer__OH,PJM +36579,40.4614,-84.7321,Mercer__OH,PJM +36580,40.5698,-84.6434,Mercer__OH,PJM +36581,40.5698,-84.6434,Mercer__OH,PJM +36582,40.4476,-84.4883,Mercer__OH,PJM +36583,40.356,-84.639,Mercer__OH,PJM +36584,39.8634,-84.2673,Montgomery__OH,PJM +36585,39.8634,-84.2673,Montgomery__OH,PJM +36586,39.8955,-84.3431,Montgomery__OH,PJM +36587,39.9442,-84.377,Miami__OH,PJM +36588,39.9442,-84.377,Miami__OH,PJM +36589,39.945,-84.3195,Miami__OH,PJM +36590,39.945,-84.3195,Miami__OH,PJM +36591,40.0631,-84.2217,Miami__OH,PJM +36592,40.151,-84.3114,Miami__OH,PJM +36593,40.1406,-84.1687,Miami__OH,PJM +36594,40.1579,-84.2146,Miami__OH,PJM +36595,39.9218,-84.2215,Montgomery__OH,PJM +36596,39.9218,-84.2215,Montgomery__OH,PJM +36597,40.0055,-84.1148,Miami__OH,PJM +36598,40.0055,-84.1148,Miami__OH,PJM +36599,39.9927,-84.2119,Miami__OH,PJM +36600,40.0954,-84.184,Miami__OH,PJM +36601,40.0487,-84.1666,Miami__OH,PJM +36602,40.0247,-84.1745,Miami__OH,PJM +36603,40.0247,-84.1745,Miami__OH,PJM +36604,40.0378,-84.3738,Miami__OH,PJM +36605,40.0378,-84.3738,Miami__OH,PJM +36606,39.5469,-81.3529,Washington__OH,PJM +36607,39.4908,-81.1584,Washington__OH,PJM +36608,39.4908,-81.1584,Washington__OH,PJM +36609,39.4908,-81.1584,Washington__OH,PJM +36610,39.4908,-81.1584,Washington__OH,PJM +36611,39.4908,-81.1584,Washington__OH,PJM +36612,39.4908,-81.1584,Washington__OH,PJM +36613,39.6489,-80.9453,Monroe__OH,PJM +36614,39.7108,-81.1225,Monroe__OH,PJM +36615,39.7457,-81.1347,Monroe__OH,PJM +36616,39.7457,-81.1347,Monroe__OH,PJM +36617,39.7457,-81.1347,Monroe__OH,PJM +36618,39.7457,-81.1347,Monroe__OH,PJM +36619,39.7457,-81.1347,Monroe__OH,PJM +36620,39.7457,-81.1347,Monroe__OH,PJM +36621,39.8937,-84.2215,Montgomery__OH,PJM +36622,39.8937,-84.2215,Montgomery__OH,PJM +36623,39.8937,-84.2215,Montgomery__OH,PJM +36624,39.8937,-84.2215,Montgomery__OH,PJM +36625,39.8937,-84.2215,Montgomery__OH,PJM +36626,39.8597,-84.2394,Montgomery__OH,PJM +36627,39.8041,-84.2526,Montgomery__OH,PJM +36628,39.9603,-84.2888,Miami__OH,PJM +36629,39.9603,-84.2888,Miami__OH,PJM +36630,39.8325,-84.3192,Montgomery__OH,PJM +36631,39.7614,-84.2978,Montgomery__OH,PJM +36632,39.7941,-84.2903,Montgomery__OH,PJM +36633,39.7945,-84.1796,Montgomery__OH,PJM +36634,39.7945,-84.1796,Montgomery__OH,PJM +36635,39.7716,-84.2031,Montgomery__OH,PJM +36636,39.857,-84.127,Montgomery__OH,PJM +36637,39.8163,-84.2196,Montgomery__OH,PJM +36638,39.8163,-84.2196,Montgomery__OH,PJM +36639,39.6869,-84.2342,Montgomery__OH,PJM +36640,39.7552,-84.329,Montgomery__OH,PJM +36641,39.8188,-84.2798,Montgomery__OH,PJM +36642,39.7762,-84.1677,Montgomery__OH,PJM +36643,39.7762,-84.1677,Montgomery__OH,PJM +36644,39.6704,-84.2358,Montgomery__OH,PJM +36645,39.6708,-84.2575,Montgomery__OH,PJM +36646,39.6708,-84.2575,Montgomery__OH,PJM +36647,39.787,-84.359,Montgomery__OH,PJM +36648,39.787,-84.359,Montgomery__OH,PJM +36649,39.787,-84.359,Montgomery__OH,PJM +36650,39.7554,-84.2471,Montgomery__OH,PJM +36651,39.8361,-84.1802,Montgomery__OH,PJM +36652,39.6932,-84.1083,Montgomery__OH,PJM +36653,39.7192,-84.0508,Greene__OH,PJM +36654,39.7192,-84.0508,Greene__OH,PJM +36655,39.7192,-84.0508,Greene__OH,PJM +36656,39.7192,-84.0508,Greene__OH,PJM +36657,39.7192,-84.0508,Greene__OH,PJM +36658,39.6176,-84.1872,Montgomery__OH,PJM +36659,39.6176,-84.1872,Montgomery__OH,PJM +36660,39.5925,-84.175,Montgomery__OH,PJM +36661,39.727,-84.201,Montgomery__OH,PJM +36662,39.7094,-84.1316,Montgomery__OH,PJM +36663,39.6557,-84.206,Montgomery__OH,PJM +36664,39.6557,-84.206,Montgomery__OH,PJM +36665,39.7129,-84.1818,Montgomery__OH,PJM +36666,39.7129,-84.1818,Montgomery__OH,PJM +36667,39.4478,-84.25,Warren__OH,PJM 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+37038,38.8944,-82.166,Gallia__OH,PJM +37039,38.8944,-82.166,Gallia__OH,PJM +37040,38.8944,-82.166,Gallia__OH,PJM +37041,39.7707,-84.1509,Montgomery__OH,PJM +37042,39.7707,-84.1509,Montgomery__OH,PJM +37043,39.7707,-84.1509,Montgomery__OH,PJM +37044,39.7707,-84.1509,Montgomery__OH,PJM +37045,39.7707,-84.1509,Montgomery__OH,PJM +37046,39.7707,-84.1509,Montgomery__OH,PJM +37047,39.7707,-84.1509,Montgomery__OH,PJM +37048,40.5376,-84.3986,Auglaize__OH,PJM +37049,40.5376,-84.3986,Auglaize__OH,PJM +37050,39.4514,-84.4444,Butler__OH,PJM +37051,39.4514,-84.4444,Butler__OH,PJM +37052,39.4514,-84.4444,Butler__OH,PJM +37053,39.4514,-84.4444,Butler__OH,PJM +37054,39.4514,-84.4444,Butler__OH,PJM +37055,39.4514,-84.4444,Butler__OH,PJM +37056,39.4514,-84.4444,Butler__OH,PJM +37057,39.4514,-84.4444,Butler__OH,PJM +37058,39.4514,-84.4444,Butler__OH,PJM +37059,39.4514,-84.4444,Butler__OH,PJM +37060,39.4514,-84.4444,Butler__OH,PJM +37061,39.4514,-84.4444,Butler__OH,PJM +37062,39.4514,-84.4444,Butler__OH,PJM +37063,40.0543,-84.6117,Darke__OH,PJM +37064,40.0543,-84.6117,Darke__OH,PJM +37065,40.0543,-84.6117,Darke__OH,PJM +37066,40.0543,-84.6117,Darke__OH,PJM +37067,39.9455,-83.0843,Franklin__OH,PJM +37068,39.9455,-83.0843,Franklin__OH,PJM +37069,39.6057,-84.2531,Montgomery__OH,PJM +37070,39.6057,-84.2531,Montgomery__OH,PJM +37071,39.6057,-84.2531,Montgomery__OH,PJM +37072,39.6057,-84.2531,Montgomery__OH,PJM +37073,39.6057,-84.2531,Montgomery__OH,PJM +37074,39.6057,-84.2531,Montgomery__OH,PJM +37075,39.6057,-84.2531,Montgomery__OH,PJM +37076,39.6057,-84.2531,Montgomery__OH,PJM +37077,39.6057,-84.2531,Montgomery__OH,PJM +37078,40.2741,-80.6382,Jefferson__OH,PJM +37079,40.2741,-80.6382,Jefferson__OH,PJM +37080,40.2741,-80.6382,Jefferson__OH,PJM +37081,40.2741,-80.6382,Jefferson__OH,PJM +37082,40.2741,-80.6382,Jefferson__OH,PJM +37083,40.2741,-80.6382,Jefferson__OH,PJM +37084,40.2741,-80.6382,Jefferson__OH,PJM +37085,40.2741,-80.6382,Jefferson__OH,PJM +37086,39.3923,-84.582,Butler__OH,PJM +37087,39.3923,-84.582,Butler__OH,PJM +37088,39.3923,-84.582,Butler__OH,PJM +37089,39.3923,-84.582,Butler__OH,PJM +37090,39.3923,-84.582,Butler__OH,PJM +37091,39.3923,-84.582,Butler__OH,PJM +37092,39.3923,-84.582,Butler__OH,PJM +37093,39.3923,-84.582,Butler__OH,PJM +37094,39.3923,-84.582,Butler__OH,PJM +37095,39.8935,-83.799,Clark__OH,PJM +37096,39.8935,-83.799,Clark__OH,PJM +37097,39.7369,-83.8179,Greene__OH,PJM +37098,39.7369,-83.8179,Greene__OH,PJM +37099,39.7369,-83.8179,Greene__OH,PJM +37100,39.7369,-83.8179,Greene__OH,PJM +37101,39.7369,-83.8179,Greene__OH,PJM +37102,39.9583,-83.0905,Franklin__OH,PJM +37103,39.9583,-83.0905,Franklin__OH,PJM +37104,39.9583,-83.0905,Franklin__OH,PJM +37105,40.4352,-83.8795,Logan__OH,PJM +37106,40.4352,-83.8795,Logan__OH,PJM +37107,39.7599,-81.0975,Monroe__OH,PJM +37108,39.7599,-81.0975,Monroe__OH,PJM +37109,39.7039,-83.1927,Pickaway__OH,PJM +37110,39.7039,-83.1927,Pickaway__OH,PJM +37111,39.7039,-83.1927,Pickaway__OH,PJM +37112,39.7039,-83.1927,Pickaway__OH,PJM +37113,39.7039,-83.1927,Pickaway__OH,PJM +37114,39.7039,-83.1927,Pickaway__OH,PJM +37115,39.7039,-83.1927,Pickaway__OH,PJM +37116,39.7039,-83.1927,Pickaway__OH,PJM +37117,39.7039,-83.1927,Pickaway__OH,PJM +37118,39.7039,-83.1927,Pickaway__OH,PJM +37119,39.7039,-83.1927,Pickaway__OH,PJM +37120,39.7039,-83.1927,Pickaway__OH,PJM +37121,40.5033,-81.4557,Tuscarawas__OH,PJM +37122,40.5033,-81.4557,Tuscarawas__OH,PJM +37123,40.5033,-81.4557,Tuscarawas__OH,PJM +37124,40.5033,-81.4557,Tuscarawas__OH,PJM +37125,40.5033,-81.4557,Tuscarawas__OH,PJM +37126,40.5033,-81.4557,Tuscarawas__OH,PJM +37127,39.9103,-80.754,Marshall__WV,PJM +37128,39.9103,-80.754,Marshall__WV,PJM +37129,39.9103,-80.754,Marshall__WV,PJM +37130,39.9103,-80.754,Marshall__WV,PJM +37131,39.9103,-80.754,Marshall__WV,PJM +37132,40.5206,-80.6093,Hancock__WV,PJM +37133,40.5206,-80.6093,Hancock__WV,PJM +37134,38.6263,-83.7043,Mason__KY,PJM +37135,38.6263,-83.7043,Mason__KY,PJM +37136,39.37,-84.5096,Butler__OH,PJM +37137,39.37,-84.5096,Butler__OH,PJM +37138,39.37,-84.5096,Butler__OH,PJM +37139,39.4635,-84.3809,Butler__OH,PJM +37140,39.4635,-84.3809,Butler__OH,PJM +37141,39.4635,-84.3809,Butler__OH,PJM +37142,39.4635,-84.3809,Butler__OH,PJM +37143,39.4635,-84.3809,Butler__OH,PJM +37144,39.4635,-84.3809,Butler__OH,PJM +37145,40.2263,-84.4738,Darke__OH,PJM +37146,40.2263,-84.4738,Darke__OH,PJM +37147,39.6017,-81.704,Morgan__OH,PJM +37148,39.6017,-81.704,Morgan__OH,PJM +37149,39.6017,-81.704,Morgan__OH,PJM +37150,39.6017,-81.704,Morgan__OH,PJM +37151,39.6017,-81.704,Morgan__OH,PJM +37152,39.6017,-81.704,Morgan__OH,PJM +37153,39.6017,-81.704,Morgan__OH,PJM +37154,39.6017,-81.704,Morgan__OH,PJM +37155,39.6017,-81.704,Morgan__OH,PJM +37156,40.7213,-83.8375,Hardin__OH,PJM +37157,40.8098,-83.8248,Hardin__OH,PJM +37158,40.8098,-83.8248,Hardin__OH,PJM +37159,40.7778,-83.6391,Hardin__OH,PJM +37160,40.8858,-83.9335,Allen__OH,PJM +37161,40.9534,-83.8712,Hancock__OH,PJM +37162,40.894,-83.8532,Hancock__OH,PJM +37163,40.8134,-84.0093,Allen__OH,PJM +37164,40.9707,-84.0339,Putnam__OH,PJM +37165,40.7952,-84.3718,Allen__OH,PJM +37166,40.8718,-84.4609,Van Wert__OH,PJM +37167,40.8718,-84.4609,Van Wert__OH,PJM +37168,40.8204,-84.3809,Van Wert__OH,PJM +37169,40.9935,-84.235,Putnam__OH,PJM +37170,41.0412,-84.2982,Putnam__OH,PJM +37171,40.62,-83.8709,Hardin__OH,PJM +37172,40.7504,-84.1651,Allen__OH,PJM +37173,40.7504,-84.1651,Allen__OH,PJM +37174,40.7504,-84.1651,Allen__OH,PJM +37175,40.7504,-84.1651,Allen__OH,PJM +37176,40.7504,-84.1651,Allen__OH,PJM +37177,40.7504,-84.1651,Allen__OH,PJM +37178,40.7378,-84.2147,Allen__OH,PJM +37179,40.7378,-84.2147,Allen__OH,PJM +37180,40.7978,-84.1228,Allen__OH,PJM +37181,40.7714,-84.048,Allen__OH,PJM +37182,40.7714,-84.048,Allen__OH,PJM +37183,40.8291,-84.1261,Allen__OH,PJM +37184,40.8435,-84.0617,Allen__OH,PJM +37185,40.751,-84.0772,Allen__OH,PJM +37186,40.8117,-84.2169,Allen__OH,PJM +37187,40.8235,-84.1452,Allen__OH,PJM +37188,40.8235,-84.1452,Allen__OH,PJM +37189,40.8235,-84.1452,Allen__OH,PJM +37190,40.7632,-84.1903,Allen__OH,PJM +37191,40.694,-84.0595,Allen__OH,PJM +37192,40.6388,-84.0319,Auglaize__OH,PJM +37193,40.6388,-84.0319,Auglaize__OH,PJM +37194,40.7059,-84.1953,Allen__OH,PJM +37195,40.7059,-84.1953,Allen__OH,PJM +37196,40.6505,-84.2515,Auglaize__OH,PJM +37197,40.724,-84.0865,Allen__OH,PJM +37198,40.724,-84.0865,Allen__OH,PJM +37199,40.6586,-84.3865,Auglaize__OH,PJM +37200,40.722,-84.3175,Allen__OH,PJM +37201,40.908,-82.3795,Ashland__OH,PJM +37202,40.908,-82.3795,Ashland__OH,PJM +37203,40.908,-82.3795,Ashland__OH,PJM +37204,40.8393,-82.2218,Ashland__OH,PJM +37205,40.8809,-82.349,Ashland__OH,PJM +37206,40.8809,-82.349,Ashland__OH,PJM +37207,40.8994,-82.4181,Richland__OH,PJM +37208,41.0476,-82.4854,Huron__OH,PJM +37209,40.6849,-82.3107,Ashland__OH,PJM +37210,40.5526,-82.1837,Knox__OH,PJM +37211,40.6587,-82.1841,Holmes__OH,PJM +37212,40.7316,-82.5179,Richland__OH,PJM +37213,40.802,-82.5268,Richland__OH,PJM +37214,40.802,-82.5268,Richland__OH,PJM +37215,40.6803,-82.4897,Richland__OH,PJM +37216,40.6803,-82.4897,Richland__OH,PJM +37217,40.6803,-82.4897,Richland__OH,PJM +37218,40.7567,-82.5571,Richland__OH,PJM +37219,40.7567,-82.5571,Richland__OH,PJM +37220,41.1186,-82.3892,Huron__OH,PJM +37221,41.0201,-82.368,Ashland__OH,PJM +37222,40.9808,-82.4738,Richland__OH,PJM +37223,41.0333,-82.1943,Ashland__OH,PJM +37224,40.9529,-82.0694,Wayne__OH,PJM +37225,40.8154,-81.8963,Wayne__OH,PJM +37226,40.765,-81.9139,Wayne__OH,PJM +37227,40.765,-81.9139,Wayne__OH,PJM +37228,40.8516,-82.0626,Wayne__OH,PJM +37229,40.8516,-82.0626,Wayne__OH,PJM +37230,40.8516,-82.0626,Wayne__OH,PJM +37231,40.8699,-81.9389,Wayne__OH,PJM +37232,41.5949,-80.6052,Ashtabula__OH,PJM +37233,41.5309,-80.5198,Ashtabula__OH,PJM +37234,41.5309,-80.5198,Ashtabula__OH,PJM +37235,41.5309,-80.5198,Ashtabula__OH,PJM +37236,41.5309,-80.5198,Ashtabula__OH,PJM +37237,41.5309,-80.5198,Ashtabula__OH,PJM +37238,41.5309,-80.5198,Ashtabula__OH,PJM +37239,41.5309,-80.5198,Ashtabula__OH,PJM +37240,41.8214,-80.793,Ashtabula__OH,PJM +37241,41.8844,-80.8544,Ashtabula__OH,PJM +37242,41.8602,-80.6589,Ashtabula__OH,PJM +37243,41.8602,-80.6589,Ashtabula__OH,PJM +37244,41.8602,-80.6589,Ashtabula__OH,PJM +37245,41.8777,-80.6508,Ashtabula__OH,PJM +37246,41.8777,-80.6508,Ashtabula__OH,PJM +37247,41.872,-80.4972,Erie__PA,PJM +37248,41.872,-80.4972,Erie__PA,PJM +37249,41.7959,-80.6783,Ashtabula__OH,PJM +37250,41.9479,-80.6174,Ashtabula__OH,PJM +37251,41.9615,-80.5713,Ashtabula__OH,PJM +37252,41.9615,-80.5713,Ashtabula__OH,PJM +37253,41.7815,-81.0225,Lake__OH,PJM +37254,41.691,-80.9442,Ashtabula__OH,PJM +37255,41.7965,-80.9343,Ashtabula__OH,PJM +37256,41.7965,-80.9343,Ashtabula__OH,PJM +37257,41.7867,-80.726,Ashtabula__OH,PJM +37258,41.717,-80.6899,Ashtabula__OH,PJM +37259,41.6744,-80.7245,Ashtabula__OH,PJM +37260,41.4806,-80.611,Trumbull__OH,PJM +37261,41.4084,-80.5003,Mercer__PA,PJM +37262,41.8067,-81.138,Lake__OH,PJM +37263,41.8014,-81.105,Lake__OH,PJM +37264,41.4745,-81.101,Geauga__OH,PJM +37265,41.4374,-80.9991,Trumbull__OH,PJM +37266,41.4155,-81.0779,Geauga__OH,PJM +37267,41.5071,-80.8415,Ashtabula__OH,PJM +37268,41.5071,-80.8415,Ashtabula__OH,PJM +37269,41.4595,-80.7701,Trumbull__OH,PJM +37270,41.5863,-80.843,Ashtabula__OH,PJM +37271,40.7688,-81.205,Stark__OH,PJM +37272,40.7688,-81.205,Stark__OH,PJM +37273,40.5683,-81.2648,Carroll__OH,PJM +37274,40.6702,-81.253,Stark__OH,PJM +37275,40.7937,-81.074,Columbiana__OH,PJM +37276,40.6878,-81.1291,Carroll__OH,PJM +37277,40.622,-80.8887,Carroll__OH,PJM +37278,40.8535,-81.0646,Columbiana__OH,PJM +37279,40.8535,-81.0646,Columbiana__OH,PJM +37280,40.8587,-81.1573,Stark__OH,PJM +37281,40.8587,-81.1573,Stark__OH,PJM +37282,40.9289,-81.2217,Stark__OH,PJM +37283,40.9163,-81.1202,Stark__OH,PJM +37284,40.8287,-80.9548,Columbiana__OH,PJM +37285,40.8508,-80.634,Columbiana__OH,PJM +37286,40.8508,-80.634,Columbiana__OH,PJM +37287,40.9038,-80.7129,Mahoning__OH,PJM +37288,40.9038,-80.7129,Mahoning__OH,PJM +37289,40.9038,-80.7129,Mahoning__OH,PJM +37290,40.7402,-80.5083,Beaver__PA,PJM +37291,40.7402,-80.5083,Beaver__PA,PJM +37292,40.741,-80.5572,Columbiana__OH,PJM +37293,40.741,-80.5572,Columbiana__OH,PJM +37294,40.741,-80.5572,Columbiana__OH,PJM +37295,40.741,-80.5572,Columbiana__OH,PJM +37296,40.741,-80.5572,Columbiana__OH,PJM +37297,40.6669,-80.5265,Columbiana__OH,PJM +37298,40.7055,-80.6776,Columbiana__OH,PJM +37299,40.8036,-80.623,Columbiana__OH,PJM +37300,40.8503,-80.4579,Beaver__PA,PJM +37301,40.8517,-80.5383,Columbiana__OH,PJM +37302,40.8517,-80.5383,Columbiana__OH,PJM +37303,40.7501,-80.9881,Columbiana__OH,PJM +37304,40.7208,-80.8258,Columbiana__OH,PJM +37305,40.8232,-80.7756,Columbiana__OH,PJM +37306,40.7085,-80.7286,Columbiana__OH,PJM +37307,40.688,-80.7896,Columbiana__OH,PJM +37308,40.8912,-80.9053,Columbiana__OH,PJM +37309,40.8912,-80.9053,Columbiana__OH,PJM +37310,40.9535,-80.9702,Mahoning__OH,PJM +37311,40.9155,-80.8579,Columbiana__OH,PJM +37312,40.9155,-80.8579,Columbiana__OH,PJM +37313,40.9566,-80.8775,Mahoning__OH,PJM +37314,40.9566,-80.8775,Mahoning__OH,PJM +37315,40.5837,-80.6085,Hancock__WV,PJM +37316,40.6012,-80.7196,Columbiana__OH,PJM +37317,41.0378,-83.0251,Seneca__OH,PJM +37318,41.0378,-83.0251,Seneca__OH,PJM +37319,40.8113,-82.9962,Crawford__OH,PJM +37320,40.8113,-82.9962,Crawford__OH,PJM +37321,40.7878,-82.9408,Crawford__OH,PJM +37322,40.8477,-82.9828,Crawford__OH,PJM +37323,40.8477,-82.9828,Crawford__OH,PJM +37324,40.6744,-82.961,Marion__OH,PJM +37325,40.6744,-82.961,Marion__OH,PJM +37326,40.8703,-82.8194,Crawford__OH,PJM +37327,40.786,-82.7731,Crawford__OH,PJM +37328,40.7382,-82.8349,Crawford__OH,PJM +37329,40.725,-82.7592,Crawford__OH,PJM +37330,40.6261,-82.8638,Morrow__OH,PJM +37331,40.8264,-83.156,Wyandot__OH,PJM +37332,40.952,-82.7855,Crawford__OH,PJM +37333,40.9024,-82.6606,Richland__OH,PJM +37334,40.824,-82.679,Richland__OH,PJM +37335,40.824,-82.679,Richland__OH,PJM +37336,40.8467,-82.4679,Richland__OH,PJM +37337,41.4652,-81.404,Cuyahoga__OH,PJM +37338,41.4652,-81.404,Cuyahoga__OH,PJM +37339,41.4652,-81.404,Cuyahoga__OH,PJM +37340,41.4383,-81.4048,Cuyahoga__OH,PJM +37341,41.42,-81.5769,Cuyahoga__OH,PJM +37342,41.42,-81.5769,Cuyahoga__OH,PJM +37343,41.4364,-81.4776,Cuyahoga__OH,PJM +37344,41.4449,-81.5914,Cuyahoga__OH,PJM +37345,41.3266,-81.5436,Summit__OH,PJM +37346,41.2457,-81.5725,Summit__OH,PJM +37347,41.2457,-81.5725,Summit__OH,PJM +37348,41.2742,-81.6439,Summit__OH,PJM +37349,41.2742,-81.6439,Summit__OH,PJM +37350,41.3667,-81.5637,Cuyahoga__OH,PJM +37351,41.3827,-81.8609,Cuyahoga__OH,PJM +37352,41.3827,-81.8609,Cuyahoga__OH,PJM +37353,41.4137,-81.9302,Cuyahoga__OH,PJM +37354,41.3999,-81.8285,Cuyahoga__OH,PJM +37355,41.3858,-81.9236,Cuyahoga__OH,PJM +37356,41.3858,-81.9236,Cuyahoga__OH,PJM +37357,41.4868,-81.3469,Geauga__OH,PJM +37358,41.5246,-81.5226,Cuyahoga__OH,PJM +37359,41.556,-81.4428,Cuyahoga__OH,PJM +37360,41.6002,-81.3847,Lake__OH,PJM +37361,41.6002,-81.3847,Lake__OH,PJM +37362,41.5296,-81.4228,Cuyahoga__OH,PJM +37363,41.5296,-81.4228,Cuyahoga__OH,PJM +37364,41.5318,-81.6635,Cuyahoga__OH,PJM +37365,41.586,-81.5613,Cuyahoga__OH,PJM +37366,41.586,-81.5613,Cuyahoga__OH,PJM +37367,41.5116,-81.6018,Cuyahoga__OH,PJM +37368,41.5116,-81.6018,Cuyahoga__OH,PJM +37369,41.5116,-81.6018,Cuyahoga__OH,PJM +37370,41.5116,-81.6018,Cuyahoga__OH,PJM +37371,41.5116,-81.6018,Cuyahoga__OH,PJM +37372,41.5116,-81.6018,Cuyahoga__OH,PJM +37373,41.5892,-81.5218,Cuyahoga__OH,PJM +37374,41.5892,-81.5218,Cuyahoga__OH,PJM +37375,41.5449,-81.5841,Cuyahoga__OH,PJM +37376,41.5449,-81.5841,Cuyahoga__OH,PJM +37377,41.4983,-81.5032,Cuyahoga__OH,PJM +37378,41.4983,-81.5032,Cuyahoga__OH,PJM +37379,41.5678,-81.5899,Cuyahoga__OH,PJM +37380,41.5261,-81.6736,Cuyahoga__OH,PJM +37381,41.5483,-81.561,Cuyahoga__OH,PJM +37382,41.5483,-81.561,Cuyahoga__OH,PJM +37383,41.4935,-81.5749,Cuyahoga__OH,PJM +37384,41.4935,-81.5749,Cuyahoga__OH,PJM +37385,41.4935,-81.5749,Cuyahoga__OH,PJM +37386,41.4584,-81.6093,Cuyahoga__OH,PJM +37387,41.4584,-81.6093,Cuyahoga__OH,PJM +37388,41.5541,-81.5184,Cuyahoga__OH,PJM +37389,41.4967,-81.6094,Cuyahoga__OH,PJM +37390,41.4947,-81.441,Cuyahoga__OH,PJM +37391,41.5141,-81.4693,Cuyahoga__OH,PJM +37392,41.5071,-81.4134,Cuyahoga__OH,PJM +37393,41.5355,-81.5315,Cuyahoga__OH,PJM +37394,41.5355,-81.5315,Cuyahoga__OH,PJM +37395,41.5355,-81.5315,Cuyahoga__OH,PJM +37396,41.5267,-81.6339,Cuyahoga__OH,PJM +37397,41.4689,-81.659,Cuyahoga__OH,PJM +37398,41.4689,-81.659,Cuyahoga__OH,PJM +37399,41.4555,-81.7172,Cuyahoga__OH,PJM +37400,41.4555,-81.7172,Cuyahoga__OH,PJM +37401,41.4969,-81.7178,Cuyahoga__OH,PJM +37402,41.4969,-81.7178,Cuyahoga__OH,PJM +37403,41.3792,-81.7289,Cuyahoga__OH,PJM +37404,41.3542,-81.7004,Cuyahoga__OH,PJM +37405,41.3542,-81.7004,Cuyahoga__OH,PJM +37406,41.4368,-81.528,Cuyahoga__OH,PJM +37407,41.4659,-81.5806,Cuyahoga__OH,PJM +37408,41.5098,-81.5785,Cuyahoga__OH,PJM +37409,41.4422,-81.8572,Cuyahoga__OH,PJM +37410,41.3716,-81.7714,Cuyahoga__OH,PJM +37411,41.494,-81.8175,Cuyahoga__OH,PJM +37412,41.4147,-81.6438,Cuyahoga__OH,PJM +37413,41.4147,-81.6438,Cuyahoga__OH,PJM +37414,41.5358,-81.6163,Cuyahoga__OH,PJM +37415,41.5358,-81.6163,Cuyahoga__OH,PJM +37416,41.4265,-81.6969,Cuyahoga__OH,PJM +37417,41.4931,-81.7816,Cuyahoga__OH,PJM +37418,41.4494,-81.6878,Cuyahoga__OH,PJM +37419,41.5181,-81.6633,Cuyahoga__OH,PJM +37420,41.3473,-81.5223,Summit__OH,PJM +37421,41.5303,-81.497,Cuyahoga__OH,PJM +37422,41.4844,-81.5521,Cuyahoga__OH,PJM +37423,41.4792,-81.8054,Cuyahoga__OH,PJM +37424,41.4713,-81.9215,Cuyahoga__OH,PJM +37425,41.4876,-81.9085,Cuyahoga__OH,PJM +37426,41.4876,-81.9085,Cuyahoga__OH,PJM +37427,41.382,-81.6063,Cuyahoga__OH,PJM +37428,41.3825,-81.495,Cuyahoga__OH,PJM +37429,41.3825,-81.495,Cuyahoga__OH,PJM +37430,41.3355,-81.6302,Cuyahoga__OH,PJM +37431,41.3355,-81.6302,Cuyahoga__OH,PJM +37432,41.3355,-81.6302,Cuyahoga__OH,PJM +37433,41.3355,-81.6302,Cuyahoga__OH,PJM +37434,41.3355,-81.6302,Cuyahoga__OH,PJM +37435,41.2981,-81.8017,Cuyahoga__OH,PJM +37436,41.3403,-81.7088,Cuyahoga__OH,PJM +37437,41.3403,-81.7088,Cuyahoga__OH,PJM +37438,41.3015,-81.7073,Cuyahoga__OH,PJM +37439,41.3015,-81.7073,Cuyahoga__OH,PJM +37440,41.4011,-81.6931,Cuyahoga__OH,PJM +37441,41.312,-81.6506,Cuyahoga__OH,PJM +37442,41.4872,-81.7448,Cuyahoga__OH,PJM +37443,41.4005,-81.7764,Cuyahoga__OH,PJM +37444,41.3865,-81.7407,Cuyahoga__OH,PJM +37445,41.2538,-81.8478,Medina__OH,PJM +37446,41.4116,-81.7244,Cuyahoga__OH,PJM +37447,41.4116,-81.7244,Cuyahoga__OH,PJM +37448,41.3811,-81.8025,Cuyahoga__OH,PJM +37449,41.6232,-81.5009,Cuyahoga__OH,PJM +37450,41.6519,-81.4507,Lake__OH,PJM +37451,41.6519,-81.4507,Lake__OH,PJM +37452,41.5566,-81.6066,Cuyahoga__OH,PJM +37453,41.5566,-81.6066,Cuyahoga__OH,PJM +37454,41.4862,-81.6819,Cuyahoga__OH,PJM +37455,41.4838,-81.8631,Cuyahoga__OH,PJM +37456,41.489,-81.7548,Cuyahoga__OH,PJM +37457,41.489,-81.7548,Cuyahoga__OH,PJM +37458,41.489,-81.7548,Cuyahoga__OH,PJM +37459,41.4351,-81.7734,Cuyahoga__OH,PJM +37460,41.4522,-81.5496,Cuyahoga__OH,PJM +37461,41.4522,-81.5496,Cuyahoga__OH,PJM +37462,41.3396,-81.5685,Summit__OH,PJM +37463,41.3396,-81.5685,Summit__OH,PJM +37464,41.5091,-81.9769,Lorain__OH,PJM +37465,41.491,-81.9818,Lorain__OH,PJM +37466,41.491,-81.9818,Lorain__OH,PJM +37467,41.3285,-81.9594,Lorain__OH,PJM +37468,41.3145,-81.9962,Lorain__OH,PJM +37469,41.2458,-81.6728,Summit__OH,PJM +37470,41.2712,-81.6896,Medina__OH,PJM +37471,41.2712,-81.7113,Medina__OH,PJM +37472,41.3458,-81.8054,Cuyahoga__OH,PJM +37473,41.3458,-81.8054,Cuyahoga__OH,PJM +37474,41.3458,-81.8054,Cuyahoga__OH,PJM +37475,41.3458,-81.8054,Cuyahoga__OH,PJM +37476,41.3458,-81.8054,Cuyahoga__OH,PJM +37477,41.3458,-81.8054,Cuyahoga__OH,PJM +37478,41.3639,-81.8303,Cuyahoga__OH,PJM +37479,41.4367,-81.8813,Cuyahoga__OH,PJM +37480,41.4367,-81.8813,Cuyahoga__OH,PJM +37481,41.3673,-81.9098,Cuyahoga__OH,PJM +37482,41.4118,-81.9682,Cuyahoga__OH,PJM +37483,41.4597,-81.8053,Cuyahoga__OH,PJM +37484,41.4597,-81.8053,Cuyahoga__OH,PJM +37485,41.3471,-81.4576,Summit__OH,PJM +37486,41.3471,-81.4576,Summit__OH,PJM +37487,41.4476,-81.3237,Geauga__OH,PJM +37488,41.4476,-81.3237,Geauga__OH,PJM +37489,41.4476,-81.3237,Geauga__OH,PJM +37490,41.4476,-81.3237,Geauga__OH,PJM +37491,41.4476,-81.3237,Geauga__OH,PJM +37492,41.4476,-81.3237,Geauga__OH,PJM +37493,41.3689,-81.3213,Geauga__OH,PJM +37494,41.2567,-81.7995,Medina__OH,PJM +37495,41.2821,-81.857,Cuyahoga__OH,PJM +37496,41.2821,-81.857,Cuyahoga__OH,PJM +37497,41.2549,-81.9122,Medina__OH,PJM +37498,41.2478,-81.6381,Summit__OH,PJM +37499,41.2478,-81.6381,Summit__OH,PJM +37500,41.3118,-81.8325,Cuyahoga__OH,PJM +37501,41.3118,-81.8325,Cuyahoga__OH,PJM +37502,41.4404,-81.979,Lorain__OH,PJM +37503,41.4404,-81.979,Lorain__OH,PJM +37504,41.4404,-81.979,Lorain__OH,PJM +37505,41.4569,-81.9026,Cuyahoga__OH,PJM +37506,41.4569,-81.9026,Cuyahoga__OH,PJM +37507,41.4569,-81.9026,Cuyahoga__OH,PJM +37508,41.4569,-81.9026,Cuyahoga__OH,PJM +37509,41.4569,-81.9026,Cuyahoga__OH,PJM +37510,41.4569,-81.9026,Cuyahoga__OH,PJM +37511,41.4605,-81.9449,Cuyahoga__OH,PJM +37512,41.2435,-84.7152,Paulding__OH,PJM +37513,41.4479,-84.6574,Williams__OH,PJM +37514,41.4537,-84.5151,Williams__OH,PJM +37515,41.1133,-84.2562,Putnam__OH,PJM +37516,41.3359,-84.3515,Defiance__OH,PJM +37517,41.286,-84.4195,Defiance__OH,PJM +37518,41.286,-84.4195,Defiance__OH,PJM +37519,41.2719,-84.3436,Defiance__OH,PJM +37520,41.3983,-84.381,Defiance__OH,PJM +37521,41.4772,-84.7825,Williams__OH,PJM +37522,41.3388,-84.8055,DeKalb__IN,PJM +37523,41.3388,-84.8055,DeKalb__IN,PJM +37524,41.3866,-84.6532,Defiance__OH,PJM +37525,41.3866,-84.6532,Defiance__OH,PJM +37526,41.2132,-84.1545,Henry__OH,PJM +37527,41.3204,-84.1312,Henry__OH,PJM +37528,41.3204,-84.1312,Henry__OH,PJM +37529,41.445,-84.1057,Henry__OH,PJM +37530,41.2868,-84.565,Defiance__OH,PJM +37531,41.2868,-84.565,Defiance__OH,PJM +37532,41.23,-82.9017,Seneca__OH,PJM +37533,41.1534,-82.7891,Huron__OH,PJM +37534,41.249,-82.8065,Huron__OH,PJM +37535,41.3159,-82.5247,Erie__OH,PJM +37536,41.3159,-82.5247,Erie__OH,PJM +37537,41.3199,-82.6165,Erie__OH,PJM +37538,41.3468,-82.5933,Erie__OH,PJM +37539,41.3468,-82.5933,Erie__OH,PJM +37540,41.2414,-82.6085,Huron__OH,PJM +37541,41.2061,-82.5576,Huron__OH,PJM +37542,41.1812,-82.5466,Huron__OH,PJM +37543,41.1812,-82.5466,Huron__OH,PJM +37544,41.3967,-82.7517,Erie__OH,PJM +37545,41.3967,-82.7517,Erie__OH,PJM +37546,41.3636,-82.7905,Erie__OH,PJM +37547,41.3636,-82.7905,Erie__OH,PJM +37548,41.3787,-82.7391,Erie__OH,PJM +37549,41.3787,-82.7391,Erie__OH,PJM +37550,41.4142,-82.7471,Erie__OH,PJM +37551,41.4142,-82.7471,Erie__OH,PJM +37552,41.3873,-82.4496,Erie__OH,PJM +37553,41.4096,-82.4065,Erie__OH,PJM +37554,41.3979,-82.3445,Lorain__OH,PJM +37555,41.2109,-82.4092,Huron__OH,PJM +37556,41.2109,-82.4092,Huron__OH,PJM +37557,41.5631,-84.3476,Fulton__OH,PJM +37558,41.5631,-84.3476,Fulton__OH,PJM +37559,41.5743,-84.0549,Fulton__OH,PJM +37560,41.5743,-84.0549,Fulton__OH,PJM +37561,41.6465,-84.0492,Fulton__OH,PJM +37562,41.3871,-83.9692,Henry__OH,PJM +37563,41.4688,-84.3958,Williams__OH,PJM +37564,41.4688,-84.3958,Williams__OH,PJM +37565,41.5806,-83.8562,Lucas__OH,PJM +37566,41.5806,-83.8562,Lucas__OH,PJM +37567,41.5806,-83.8562,Lucas__OH,PJM +37568,41.6,-83.9336,Fulton__OH,PJM +37569,41.6,-83.9336,Fulton__OH,PJM +37570,41.7072,-84.1437,Fulton__OH,PJM +37571,41.7072,-84.1437,Fulton__OH,PJM +37572,41.6856,-84.1429,Fulton__OH,PJM +37573,41.5815,-84.1953,Fulton__OH,PJM +37574,41.6083,-84.5007,Williams__OH,PJM +37575,41.63,-84.296,Fulton__OH,PJM +37576,41.2922,-81.4018,Summit__OH,PJM +37577,41.3275,-81.387,Portage__OH,PJM +37578,41.3167,-81.3374,Portage__OH,PJM +37579,41.3167,-81.3374,Portage__OH,PJM +37580,41.3764,-81.264,Geauga__OH,PJM +37581,41.392,-81.1431,Geauga__OH,PJM +37582,41.392,-81.1431,Geauga__OH,PJM +37583,41.3962,-81.3273,Geauga__OH,PJM +37584,41.2926,-81.2249,Portage__OH,PJM +37585,41.5475,-81.1394,Geauga__OH,PJM +37586,41.5475,-81.1394,Geauga__OH,PJM +37587,41.5621,-81.2394,Geauga__OH,PJM +37588,41.6175,-81.2361,Geauga__OH,PJM +37589,41.6175,-81.2361,Geauga__OH,PJM +37590,41.5542,-81.2747,Geauga__OH,PJM +37591,41.461,-81.2691,Geauga__OH,PJM +37592,41.461,-81.2691,Geauga__OH,PJM +37593,41.2622,-81.0994,Portage__OH,PJM +37594,41.308,-81.055,Portage__OH,PJM +37595,41.6265,-80.9934,Ashtabula__OH,PJM +37596,41.6872,-81.3356,Lake__OH,PJM +37597,41.6789,-81.3297,Lake__OH,PJM +37598,41.6789,-81.3297,Lake__OH,PJM +37599,41.699,-81.3773,Lake__OH,PJM +37600,41.699,-81.3773,Lake__OH,PJM +37601,41.676,-81.2973,Lake__OH,PJM +37602,41.6539,-81.3744,Lake__OH,PJM +37603,41.2801,-83.5225,Wood__OH,PJM +37604,41.2801,-83.5225,Wood__OH,PJM +37605,40.9434,-83.2941,Wyandot__OH,PJM +37606,40.9434,-83.2941,Wyandot__OH,PJM +37607,40.9927,-83.3318,Seneca__OH,PJM +37608,40.9927,-83.3318,Seneca__OH,PJM +37609,41.2762,-83.9314,Henry__OH,PJM +37610,41.2762,-83.9314,Henry__OH,PJM +37611,40.9594,-83.5681,Hancock__OH,PJM +37612,40.9594,-83.5681,Hancock__OH,PJM +37613,40.9594,-83.5681,Hancock__OH,PJM +37614,40.9594,-83.5681,Hancock__OH,PJM +37615,40.9594,-83.5681,Hancock__OH,PJM +37616,41.0353,-83.6277,Hancock__OH,PJM +37617,40.9893,-83.5785,Hancock__OH,PJM +37618,41.0281,-83.6449,Hancock__OH,PJM +37619,41.0324,-83.6613,Hancock__OH,PJM +37620,41.0324,-83.6613,Hancock__OH,PJM +37621,41.0324,-83.6613,Hancock__OH,PJM +37622,40.7533,-83.5025,Hardin__OH,PJM +37623,41.2231,-83.4196,Seneca__OH,PJM +37624,41.2231,-83.4196,Seneca__OH,PJM +37625,41.2047,-83.3576,Seneca__OH,PJM +37626,41.2291,-83.3706,Seneca__OH,PJM +37627,41.1402,-83.3889,Seneca__OH,PJM +37628,41.1624,-84.0224,Putnam__OH,PJM +37629,41.1624,-84.0224,Putnam__OH,PJM +37630,41.1286,-83.8932,Putnam__OH,PJM +37631,41.002,-83.8258,Hancock__OH,PJM +37632,41.002,-83.8258,Hancock__OH,PJM +37633,40.88,-83.4765,Wyandot__OH,PJM +37634,41.1588,-83.6381,Hancock__OH,PJM +37635,41.1588,-83.6381,Hancock__OH,PJM +37636,40.6971,-83.6553,Hardin__OH,PJM +37637,40.6894,-83.629,Hardin__OH,PJM +37638,40.6894,-83.629,Hardin__OH,PJM +37639,40.6062,-81.6682,Holmes__OH,PJM +37640,40.5564,-81.7409,Holmes__OH,PJM +37641,40.6195,-81.8753,Holmes__OH,PJM +37642,40.6195,-81.8753,Holmes__OH,PJM +37643,40.6745,-81.997,Wayne__OH,PJM +37644,40.6208,-82.0661,Holmes__OH,PJM +37645,40.6208,-82.0661,Holmes__OH,PJM +37646,40.6208,-82.0661,Holmes__OH,PJM +37647,41.0996,-82.7393,Huron__OH,PJM +37648,41.0996,-82.7393,Huron__OH,PJM +37649,41.155,-82.655,Huron__OH,PJM +37650,41.0841,-82.6787,Huron__OH,PJM +37651,41.0841,-82.6787,Huron__OH,PJM +37652,41.0841,-82.6787,Huron__OH,PJM +37653,41.0841,-82.6787,Huron__OH,PJM +37654,41.0841,-82.6787,Huron__OH,PJM +37655,41.6051,-81.4396,Lake__OH,PJM +37656,41.5962,-81.5523,Cuyahoga__OH,PJM +37657,41.5962,-81.5523,Cuyahoga__OH,PJM +37658,41.6132,-81.3558,Lake__OH,PJM +37659,41.6132,-81.3558,Lake__OH,PJM +37660,41.6132,-81.3558,Lake__OH,PJM +37661,41.6784,-81.1386,Lake__OH,PJM +37662,41.7289,-81.2221,Lake__OH,PJM +37663,41.7289,-81.2221,Lake__OH,PJM +37664,41.6955,-81.2863,Lake__OH,PJM +37665,41.6757,-81.2786,Lake__OH,PJM +37666,41.7823,-81.1954,Lake__OH,PJM +37667,41.7823,-81.1954,Lake__OH,PJM +37668,41.7141,-81.1304,Lake__OH,PJM +37669,41.6037,-81.5149,Cuyahoga__OH,PJM +37670,41.6037,-81.5149,Cuyahoga__OH,PJM +37671,41.598,-81.4577,Lake__OH,PJM +37672,41.587,-81.3112,Lake__OH,PJM +37673,41.6961,-81.2594,Lake__OH,PJM +37674,41.6961,-81.2594,Lake__OH,PJM +37675,41.6438,-81.3441,Lake__OH,PJM +37676,41.3318,-82.3906,Erie__OH,PJM +37677,41.3771,-82.3125,Lorain__OH,PJM +37678,41.3496,-82.1883,Lorain__OH,PJM +37679,41.4404,-82.2426,Lorain__OH,PJM +37680,41.458,-82.0568,Lorain__OH,PJM +37681,41.4979,-81.9564,Cuyahoga__OH,PJM +37682,41.4257,-82.0626,Lorain__OH,PJM +37683,41.4149,-82.0053,Lorain__OH,PJM +37684,41.4149,-82.0053,Lorain__OH,PJM +37685,41.3572,-82.0184,Lorain__OH,PJM +37686,41.332,-82.1383,Lorain__OH,PJM +37687,41.332,-82.1383,Lorain__OH,PJM +37688,41.332,-82.1383,Lorain__OH,PJM +37689,41.3512,-82.2318,Lorain__OH,PJM +37690,41.3512,-82.2318,Lorain__OH,PJM +37691,41.3439,-82.123,Lorain__OH,PJM +37692,41.477,-82.1565,Lorain__OH,PJM +37693,41.412,-82.2545,Lorain__OH,PJM +37694,41.1806,-82.0205,Medina__OH,PJM +37695,41.1806,-82.0205,Medina__OH,PJM +37696,41.1953,-82.0945,Lorain__OH,PJM +37697,41.2737,-82.1047,Lorain__OH,PJM +37698,41.2737,-82.1047,Lorain__OH,PJM +37699,41.2006,-82.1715,Lorain__OH,PJM +37700,41.2006,-82.1715,Lorain__OH,PJM +37701,41.4286,-82.2945,Lorain__OH,PJM +37702,41.4608,-82.2009,Lorain__OH,PJM +37703,41.449,-82.1689,Lorain__OH,PJM +37704,41.449,-82.1689,Lorain__OH,PJM +37705,41.449,-82.1689,Lorain__OH,PJM +37706,41.4142,-82.1297,Lorain__OH,PJM +37707,41.4064,-82.1657,Lorain__OH,PJM +37708,41.1307,-81.7778,Medina__OH,PJM +37709,41.2156,-81.7659,Medina__OH,PJM +37710,41.1481,-81.8725,Medina__OH,PJM +37711,41.0869,-81.8863,Medina__OH,PJM +37712,41.0869,-81.8863,Medina__OH,PJM +37713,41.0869,-81.8863,Medina__OH,PJM +37714,41.0869,-81.8863,Medina__OH,PJM +37715,41.0869,-81.8863,Medina__OH,PJM +37716,41.0999,-81.935,Medina__OH,PJM +37717,41.4522,-82.0249,Lorain__OH,PJM +37718,41.4522,-82.0249,Lorain__OH,PJM +37719,41.3499,-82.0699,Lorain__OH,PJM +37720,41.3138,-82.0153,Lorain__OH,PJM +37721,41.3275,-82.0469,Lorain__OH,PJM +37722,41.2772,-82.2076,Lorain__OH,PJM +37723,41.2772,-82.2076,Lorain__OH,PJM +37724,41.2756,-82.2499,Lorain__OH,PJM +37725,41.1239,-82.2105,Lorain__OH,PJM +37726,41.1877,-82.3088,Lorain__OH,PJM +37727,41.6559,-83.2473,Lucas__OH,PJM +37728,41.6559,-83.2473,Lucas__OH,PJM +37729,41.6002,-83.8322,Lucas__OH,PJM +37730,41.5961,-83.7621,Lucas__OH,PJM +37731,41.5467,-83.7157,Lucas__OH,PJM +37732,41.639,-83.7345,Lucas__OH,PJM +37733,41.639,-83.7345,Lucas__OH,PJM +37734,41.639,-83.7345,Lucas__OH,PJM +37735,41.5869,-83.659,Lucas__OH,PJM +37736,41.628,-83.8092,Lucas__OH,PJM +37737,41.571,-83.4792,Wood__OH,PJM +37738,41.571,-83.4792,Wood__OH,PJM +37739,41.687,-83.3707,Lucas__OH,PJM +37740,41.5936,-83.3838,Ottawa__OH,PJM +37741,41.5936,-83.3838,Ottawa__OH,PJM +37742,41.5936,-83.3838,Ottawa__OH,PJM +37743,41.6925,-83.4709,Lucas__OH,PJM +37744,41.6568,-83.7341,Lucas__OH,PJM +37745,41.6568,-83.7341,Lucas__OH,PJM +37746,41.7023,-83.7491,Lucas__OH,PJM +37747,41.7023,-83.7491,Lucas__OH,PJM +37748,41.7233,-83.7217,Lucas__OH,PJM +37749,41.6729,-83.7672,Lucas__OH,PJM +37750,41.682,-83.5866,Lucas__OH,PJM +37751,41.6868,-83.5261,Lucas__OH,PJM +37752,41.763,-83.51,Monroe__MI,LRZ2_7 +37753,41.763,-83.51,Monroe__MI,LRZ2_7 +37754,41.7849,-83.542,Monroe__MI,LRZ2_7 +37755,41.7849,-83.542,Monroe__MI,LRZ2_7 +37756,41.7849,-83.542,Monroe__MI,LRZ2_7 +37757,41.7037,-83.6073,Lucas__OH,PJM +37758,41.7037,-83.6073,Lucas__OH,PJM +37759,41.6507,-83.5752,Lucas__OH,PJM +37760,41.6654,-83.3275,Lucas__OH,PJM +37761,41.6654,-83.3275,Lucas__OH,PJM +37762,41.6637,-83.5012,Lucas__OH,PJM +37763,41.6637,-83.5012,Lucas__OH,PJM +37764,41.6499,-83.3938,Lucas__OH,PJM +37765,41.7499,-83.6232,Monroe__MI,LRZ2_7 +37766,41.7499,-83.6232,Monroe__MI,LRZ2_7 +37767,41.6577,-83.672,Lucas__OH,PJM +37768,41.7116,-83.6474,Lucas__OH,PJM +37769,41.6161,-83.5014,Wood__OH,PJM +37770,41.5805,-83.6324,Lucas__OH,PJM +37771,41.6496,-83.6251,Lucas__OH,PJM +37772,41.6758,-83.6268,Lucas__OH,PJM +37773,41.6758,-83.6268,Lucas__OH,PJM +37774,41.6758,-83.6268,Lucas__OH,PJM +37775,41.6855,-83.6608,Lucas__OH,PJM +37776,41.6258,-83.5424,Lucas__OH,PJM +37777,41.5823,-83.4225,Wood__OH,PJM +37778,41.6655,-83.5875,Lucas__OH,PJM +37779,41.6461,-83.5314,Lucas__OH,PJM +37780,41.7438,-83.4364,Monroe__MI,LRZ2_7 +37781,41.6702,-83.5544,Lucas__OH,PJM +37782,41.6702,-83.5544,Lucas__OH,PJM +37783,41.6445,-83.493,Lucas__OH,PJM +37784,41.6025,-83.6002,Lucas__OH,PJM +37785,41.6025,-83.6002,Lucas__OH,PJM +37786,41.6025,-83.6002,Lucas__OH,PJM +37787,41.5397,-83.5862,Wood__OH,PJM +37788,41.5988,-83.6297,Lucas__OH,PJM +37789,41.5907,-83.5669,Wood__OH,PJM +37790,41.507,-83.7558,Lucas__OH,PJM +37791,41.4434,-83.826,Lucas__OH,PJM +37792,41.4434,-83.826,Lucas__OH,PJM +37793,41.4434,-83.826,Lucas__OH,PJM +37794,41.4434,-83.826,Lucas__OH,PJM +37795,41.4434,-83.826,Lucas__OH,PJM +37796,41.4434,-83.826,Lucas__OH,PJM +37797,41.0189,-80.7869,Mahoning__OH,PJM +37798,40.9457,-80.7249,Mahoning__OH,PJM +37799,40.9457,-80.7249,Mahoning__OH,PJM +37800,40.9973,-80.7879,Mahoning__OH,PJM +37801,41.1859,-80.5578,Trumbull__OH,PJM +37802,41.1525,-80.4681,Mercer__PA,PJM +37803,41.1525,-80.4681,Mercer__PA,PJM +37804,41.2175,-80.5514,Trumbull__OH,PJM +37805,41.2175,-80.5514,Trumbull__OH,PJM +37806,41.2175,-80.5514,Trumbull__OH,PJM +37807,41.2175,-80.5514,Trumbull__OH,PJM +37808,41.2175,-80.5514,Trumbull__OH,PJM +37809,41.0401,-80.4614,Lawrence__PA,PJM +37810,41.1407,-80.9641,Trumbull__OH,PJM +37811,41.1407,-80.9641,Trumbull__OH,PJM +37812,41.2053,-80.9241,Trumbull__OH,PJM +37813,41.2517,-81.0242,Portage__OH,PJM +37814,40.9998,-81.0526,Portage__OH,PJM +37815,41.1115,-80.6291,Mahoning__OH,PJM +37816,41.1115,-80.6291,Mahoning__OH,PJM +37817,41.2111,-80.9883,Trumbull__OH,PJM +37818,41.0115,-80.8948,Mahoning__OH,PJM +37819,41.1441,-80.5959,Trumbull__OH,PJM +37820,41.1848,-80.7223,Trumbull__OH,PJM +37821,41.1484,-80.6767,Trumbull__OH,PJM +37822,41.1484,-80.6767,Trumbull__OH,PJM +37823,41.0797,-80.6675,Mahoning__OH,PJM +37824,41.044,-80.6603,Mahoning__OH,PJM +37825,41.102,-80.6466,Mahoning__OH,PJM +37826,41.102,-80.6466,Mahoning__OH,PJM +37827,41.1251,-80.8206,Mahoning__OH,PJM +37828,41.1251,-80.8206,Mahoning__OH,PJM +37829,41.029,-80.7555,Mahoning__OH,PJM +37830,41.0909,-80.6974,Mahoning__OH,PJM +37831,41.0482,-80.7082,Mahoning__OH,PJM +37832,41.0482,-80.7082,Mahoning__OH,PJM +37833,40.9718,-80.7133,Mahoning__OH,PJM +37834,40.9718,-80.7133,Mahoning__OH,PJM +37835,41.0546,-80.7299,Mahoning__OH,PJM +37836,41.011,-80.678,Mahoning__OH,PJM +37837,40.9946,-80.6108,Mahoning__OH,PJM +37838,40.9946,-80.6108,Mahoning__OH,PJM +37839,40.9946,-80.6108,Mahoning__OH,PJM +37840,40.9946,-80.6108,Mahoning__OH,PJM +37841,40.9946,-80.6108,Mahoning__OH,PJM +37842,41.0145,-80.6573,Mahoning__OH,PJM +37843,40.9187,-80.6356,Mahoning__OH,PJM +37844,40.9538,-80.6113,Mahoning__OH,PJM +37845,40.9538,-80.6113,Mahoning__OH,PJM +37846,41.0505,-80.6222,Mahoning__OH,PJM +37847,41.0505,-80.6222,Mahoning__OH,PJM +37848,41.1262,-81.725,Medina__OH,PJM +37849,41.2051,-81.6234,Summit__OH,PJM +37850,41.1262,-81.6457,Summit__OH,PJM +37851,41.1262,-81.6457,Summit__OH,PJM +37852,41.0109,-81.732,Medina__OH,PJM +37853,41.0109,-81.732,Medina__OH,PJM +37854,40.9125,-81.6514,Wayne__OH,PJM +37855,40.9125,-81.6514,Wayne__OH,PJM +37856,41.0569,-81.5865,Summit__OH,PJM +37857,41.0569,-81.5865,Summit__OH,PJM +37858,40.9989,-81.6112,Summit__OH,PJM +37859,40.9989,-81.6112,Summit__OH,PJM +37860,41.0502,-81.6172,Summit__OH,PJM +37861,41.0502,-81.6172,Summit__OH,PJM +37862,41.322,-81.7722,Cuyahoga__OH,PJM +37863,41.2825,-81.8191,Cuyahoga__OH,PJM +37864,41.2677,-81.7238,Medina__OH,PJM +37865,41.2677,-81.7238,Medina__OH,PJM +37866,41.2011,-81.8968,Medina__OH,PJM +37867,41.2011,-81.8968,Medina__OH,PJM +37868,41.0215,-81.9153,Medina__OH,PJM +37869,40.9529,-81.8728,Wayne__OH,PJM +37870,41.1023,-82.0411,Medina__OH,PJM +37871,41.1023,-82.0411,Medina__OH,PJM +37872,40.9629,-82.1605,Ashland__OH,PJM +37873,40.8967,-81.7575,Wayne__OH,PJM +37874,41.0717,-81.7315,Medina__OH,PJM +37875,41.0717,-81.7315,Medina__OH,PJM +37876,41.0717,-81.7843,Medina__OH,PJM +37877,41.0717,-81.7843,Medina__OH,PJM +37878,41.0717,-81.7843,Medina__OH,PJM +37879,41.0313,-81.7076,Medina__OH,PJM +37880,40.6628,-84.6169,Mercer__OH,PJM +37881,40.6628,-84.6169,Mercer__OH,PJM +37882,40.7484,-84.7782,Van Wert__OH,PJM +37883,40.6189,-82.6231,Richland__OH,PJM +37884,40.5699,-82.6564,Morrow__OH,PJM +37885,40.7087,-82.5699,Richland__OH,PJM +37886,41.5051,-83.4765,Wood__OH,PJM +37887,41.4813,-83.3522,Sandusky__OH,PJM +37888,41.4813,-83.3522,Sandusky__OH,PJM +37889,41.4263,-82.8126,Erie__OH,PJM +37890,41.4868,-82.7082,Ottawa__OH,PJM +37891,41.4868,-82.7082,Ottawa__OH,PJM +37892,41.5009,-82.8038,Ottawa__OH,PJM +37893,41.5009,-82.8038,Ottawa__OH,PJM +37894,41.4964,-83.0768,Ottawa__OH,PJM +37895,41.4964,-83.0768,Ottawa__OH,PJM +37896,41.533,-83.1318,Ottawa__OH,PJM +37897,41.533,-83.1318,Ottawa__OH,PJM +37898,41.4981,-83.2313,Ottawa__OH,PJM +37899,41.5241,-82.9693,Ottawa__OH,PJM +37900,41.4894,-82.899,Ottawa__OH,PJM +37901,41.3835,-83.0219,Sandusky__OH,PJM +37902,40.9522,-84.734,Van Wert__OH,PJM +37903,40.9522,-84.734,Van Wert__OH,PJM +37904,41.0845,-84.3801,Paulding__OH,PJM +37905,41.087,-84.6279,Paulding__OH,PJM +37906,41.1603,-84.6006,Paulding__OH,PJM +37907,41.0664,-84.724,Paulding__OH,PJM +37908,41.0023,-81.576,Summit__OH,PJM +37909,41.0023,-81.576,Summit__OH,PJM +37910,41.0023,-81.576,Summit__OH,PJM +37911,41.0023,-81.576,Summit__OH,PJM +37912,41.0023,-81.576,Summit__OH,PJM +37913,40.9385,-81.4807,Summit__OH,PJM +37914,41.1114,-81.43,Summit__OH,PJM +37915,41.1114,-81.43,Summit__OH,PJM +37916,41.0197,-81.1546,Portage__OH,PJM +37917,41.0631,-81.0624,Portage__OH,PJM +37918,41.0631,-81.0624,Portage__OH,PJM +37919,41.3226,-81.4862,Summit__OH,PJM +37920,41.3226,-81.4862,Summit__OH,PJM +37921,41.3226,-81.4862,Summit__OH,PJM +37922,41.1918,-81.4563,Summit__OH,PJM +37923,41.282,-81.3693,Portage__OH,PJM +37924,41.2574,-81.4252,Summit__OH,PJM +37925,41.1343,-81.3596,Portage__OH,PJM +37926,41.1343,-81.3596,Portage__OH,PJM +37927,41.0886,-81.3739,Portage__OH,PJM +37928,41.1634,-81.2338,Portage__OH,PJM +37929,41.1634,-81.2338,Portage__OH,PJM +37930,41.1634,-81.2338,Portage__OH,PJM +37931,41.1634,-81.2338,Portage__OH,PJM +37932,41.1634,-81.2338,Portage__OH,PJM +37933,41.1634,-81.2338,Portage__OH,PJM +37934,41.1634,-81.2338,Portage__OH,PJM +37935,41.1739,-81.293,Portage__OH,PJM +37936,41.3327,-81.2305,Portage__OH,PJM +37937,41.3327,-81.2305,Portage__OH,PJM +37938,41.2922,-81.1317,Portage__OH,PJM +37939,41.0024,-81.3311,Portage__OH,PJM +37940,40.9819,-81.3823,Stark__OH,PJM +37941,41.0587,-81.3147,Portage__OH,PJM +37942,41.139,-81.2224,Portage__OH,PJM +37943,41.2697,-81.2399,Portage__OH,PJM +37944,41.1906,-81.1567,Portage__OH,PJM +37945,41.2047,-81.4827,Summit__OH,PJM +37946,41.2281,-81.3976,Summit__OH,PJM +37947,41.1614,-81.4593,Summit__OH,PJM +37948,41.2414,-81.3764,Portage__OH,PJM +37949,41.1527,-81.3381,Portage__OH,PJM +37950,41.1021,-81.3996,Summit__OH,PJM +37951,41.1021,-81.3996,Summit__OH,PJM +37952,41.0424,-84.072,Putnam__OH,PJM +37953,41.0574,-84.1047,Putnam__OH,PJM +37954,41.0574,-84.1047,Putnam__OH,PJM +37955,41.0574,-84.1047,Putnam__OH,PJM +37956,41.0015,-83.9653,Putnam__OH,PJM +37957,40.6789,-82.4274,Richland__OH,PJM +37958,40.8053,-82.4162,Richland__OH,PJM +37959,40.7636,-82.455,Richland__OH,PJM +37960,40.7695,-82.6193,Richland__OH,PJM +37961,40.6508,-82.5573,Richland__OH,PJM +37962,40.745,-82.4329,Richland__OH,PJM +37963,41.3491,-83.0031,Sandusky__OH,PJM +37964,41.2801,-83.0226,Sandusky__OH,PJM +37965,41.4324,-83.007,Sandusky__OH,PJM +37966,41.3876,-83.1541,Sandusky__OH,PJM +37967,41.3876,-83.1541,Sandusky__OH,PJM +37968,41.3669,-83.1698,Sandusky__OH,PJM +37969,41.3402,-83.1442,Sandusky__OH,PJM +37970,41.3823,-83.1012,Sandusky__OH,PJM +37971,41.3747,-83.3257,Sandusky__OH,PJM +37972,41.3214,-83.4021,Sandusky__OH,PJM +37973,41.3578,-83.2356,Sandusky__OH,PJM +37974,41.1906,-83.0195,Seneca__OH,PJM +37975,41.1538,-83.0946,Seneca__OH,PJM +37976,41.0289,-83.1432,Seneca__OH,PJM +37977,41.1417,-83.1464,Seneca__OH,PJM +37978,41.1071,-83.0627,Seneca__OH,PJM +37979,40.6408,-81.4767,Tuscarawas__OH,PJM +37980,40.6408,-81.4767,Tuscarawas__OH,PJM +37981,40.8415,-81.5346,Stark__OH,PJM +37982,40.8415,-81.5346,Stark__OH,PJM +37983,40.8652,-81.6208,Stark__OH,PJM +37984,40.9085,-81.5641,Stark__OH,PJM +37985,40.9427,-81.3526,Stark__OH,PJM +37986,40.9217,-81.2895,Stark__OH,PJM +37987,40.9217,-81.2895,Stark__OH,PJM +37988,40.8715,-81.5398,Stark__OH,PJM +37989,40.8547,-81.4207,Stark__OH,PJM +37990,40.8322,-81.4916,Stark__OH,PJM +37991,40.8178,-81.3632,Stark__OH,PJM +37992,40.8178,-81.3632,Stark__OH,PJM +37993,40.8507,-81.3303,Stark__OH,PJM +37994,40.8507,-81.3303,Stark__OH,PJM +37995,40.8914,-81.3003,Stark__OH,PJM +37996,40.8914,-81.3003,Stark__OH,PJM +37997,40.8924,-81.3912,Stark__OH,PJM +37998,40.8924,-81.3912,Stark__OH,PJM +37999,40.7713,-81.3724,Stark__OH,PJM +38000,40.8478,-81.4718,Stark__OH,PJM +38001,40.7845,-81.3543,Stark__OH,PJM +38002,40.7724,-81.5147,Stark__OH,PJM +38003,40.7545,-81.3059,Stark__OH,PJM +38004,40.8655,-81.3592,Stark__OH,PJM +38005,40.8655,-81.3592,Stark__OH,PJM +38006,40.7159,-81.3802,Stark__OH,PJM +38007,40.7159,-81.3802,Stark__OH,PJM +38008,40.705,-81.468,Stark__OH,PJM +38009,40.7914,-81.4632,Stark__OH,PJM +38010,40.779,-81.3924,Stark__OH,PJM +38011,40.779,-81.3924,Stark__OH,PJM +38012,40.9487,-81.5762,Summit__OH,PJM +38013,40.7099,-81.6799,Wayne__OH,PJM +38014,40.9021,-81.2082,Stark__OH,PJM +38015,40.8616,-81.2377,Stark__OH,PJM +38016,40.8246,-81.2745,Stark__OH,PJM +38017,40.8954,-81.4581,Stark__OH,PJM +38018,40.8954,-81.4581,Stark__OH,PJM +38019,40.813,-81.5467,Stark__OH,PJM +38020,40.8123,-81.6,Stark__OH,PJM +38021,40.7479,-81.4613,Stark__OH,PJM +38022,40.7479,-81.4613,Stark__OH,PJM +38023,40.7669,-81.6269,Stark__OH,PJM +38024,40.7506,-81.5922,Stark__OH,PJM +38025,40.7506,-81.5922,Stark__OH,PJM +38026,40.8192,-81.6622,Wayne__OH,PJM +38027,40.6872,-81.5208,Stark__OH,PJM +38028,40.9054,-81.4953,Stark__OH,PJM +38029,40.8459,-81.4319,Stark__OH,PJM +38030,40.8459,-81.4319,Stark__OH,PJM +38031,40.8459,-81.4319,Stark__OH,PJM +38032,41.0353,-81.4328,Summit__OH,PJM +38033,40.9543,-81.4014,Stark__OH,PJM +38034,40.9175,-81.4259,Summit__OH,PJM +38035,40.9175,-81.4259,Summit__OH,PJM +38036,40.8584,-81.4442,Stark__OH,PJM +38037,40.8584,-81.4442,Stark__OH,PJM +38038,40.904,-81.3611,Stark__OH,PJM +38039,40.904,-81.3611,Stark__OH,PJM +38040,40.9493,-81.4362,Summit__OH,PJM +38041,40.9493,-81.4362,Summit__OH,PJM +38042,41.1045,-81.5874,Summit__OH,PJM +38043,41.1045,-81.5874,Summit__OH,PJM +38044,41.1377,-81.5212,Summit__OH,PJM +38045,41.1741,-81.5871,Summit__OH,PJM +38046,41.1065,-81.4548,Summit__OH,PJM +38047,41.1065,-81.4548,Summit__OH,PJM +38048,41.0672,-81.4543,Summit__OH,PJM +38049,41.0672,-81.4543,Summit__OH,PJM +38050,41.0672,-81.4543,Summit__OH,PJM +38051,41.0672,-81.4543,Summit__OH,PJM +38052,41.0672,-81.4543,Summit__OH,PJM +38053,41.0368,-81.5608,Summit__OH,PJM +38054,41.0703,-81.5567,Summit__OH,PJM +38055,41.0981,-81.531,Summit__OH,PJM +38056,41.1529,-81.5624,Summit__OH,PJM +38057,40.9802,-81.6495,Wayne__OH,PJM +38058,41.0121,-81.4787,Summit__OH,PJM +38059,41.0922,-81.6359,Summit__OH,PJM +38060,41.1009,-81.4882,Summit__OH,PJM +38061,41.0286,-81.4744,Summit__OH,PJM +38062,41.0644,-81.4786,Summit__OH,PJM +38063,40.9757,-81.507,Summit__OH,PJM +38064,40.9757,-81.507,Summit__OH,PJM +38065,41.0146,-81.5085,Summit__OH,PJM +38066,40.9277,-81.5271,Summit__OH,PJM +38067,41.193,-81.5885,Summit__OH,PJM +38068,41.234,-81.5984,Summit__OH,PJM +38069,41.1485,-81.4561,Summit__OH,PJM +38070,41.0691,-81.4032,Summit__OH,PJM +38071,41.0691,-81.4032,Summit__OH,PJM +38072,41.0769,-81.5293,Summit__OH,PJM +38073,41.0769,-81.5293,Summit__OH,PJM +38074,41.0769,-81.5293,Summit__OH,PJM +38075,41.3365,-81.5987,Cuyahoga__OH,PJM +38076,41.3365,-81.5987,Cuyahoga__OH,PJM +38077,41.2962,-81.5767,Cuyahoga__OH,PJM +38078,41.2962,-81.5767,Cuyahoga__OH,PJM +38079,41.3077,-81.4449,Summit__OH,PJM +38080,41.3077,-81.4449,Summit__OH,PJM +38081,41.293,-81.5062,Summit__OH,PJM +38082,41.3782,-81.3694,Geauga__OH,PJM +38083,41.2207,-81.3642,Portage__OH,PJM +38084,41.3265,-81.4278,Summit__OH,PJM +38085,41.398,-80.8258,Trumbull__OH,PJM +38086,41.398,-80.8258,Trumbull__OH,PJM +38087,41.3273,-80.6492,Trumbull__OH,PJM +38088,41.3492,-80.7011,Trumbull__OH,PJM +38089,41.3722,-80.7511,Trumbull__OH,PJM +38090,41.3722,-80.7511,Trumbull__OH,PJM +38091,41.1611,-80.6373,Trumbull__OH,PJM +38092,41.1611,-80.6373,Trumbull__OH,PJM +38093,41.1974,-80.6963,Trumbull__OH,PJM +38094,41.1974,-80.6963,Trumbull__OH,PJM +38095,41.1974,-80.6963,Trumbull__OH,PJM +38096,41.3205,-80.5557,Trumbull__OH,PJM +38097,41.3205,-80.5557,Trumbull__OH,PJM +38098,41.2494,-80.5761,Trumbull__OH,PJM +38099,41.2282,-80.6751,Trumbull__OH,PJM +38100,41.2282,-80.6751,Trumbull__OH,PJM +38101,41.2052,-80.776,Trumbull__OH,PJM +38102,41.3334,-80.9791,Trumbull__OH,PJM +38103,41.3334,-80.9791,Trumbull__OH,PJM +38104,41.2823,-80.8313,Trumbull__OH,PJM +38105,41.3083,-80.8117,Trumbull__OH,PJM +38106,41.2017,-80.6733,Trumbull__OH,PJM +38107,41.2017,-80.6733,Trumbull__OH,PJM +38108,41.1673,-80.8907,Trumbull__OH,PJM +38109,41.3333,-80.8426,Trumbull__OH,PJM +38110,41.2836,-80.9299,Trumbull__OH,PJM +38111,41.3066,-80.7725,Trumbull__OH,PJM +38112,41.2367,-80.7803,Trumbull__OH,PJM +38113,41.2152,-80.7432,Trumbull__OH,PJM +38114,41.2603,-80.7544,Trumbull__OH,PJM +38115,41.2603,-80.7544,Trumbull__OH,PJM +38116,40.6297,-81.5871,Tuscarawas__OH,PJM +38117,40.9689,-84.6043,Van Wert__OH,PJM +38118,40.9253,-84.5754,Van Wert__OH,PJM +38119,40.9056,-84.6477,Van Wert__OH,PJM +38120,40.6717,-81.7445,Wayne__OH,PJM +38121,40.6717,-81.7445,Wayne__OH,PJM +38122,40.7097,-81.8046,Wayne__OH,PJM +38123,40.7097,-81.8046,Wayne__OH,PJM +38124,40.7827,-81.7829,Wayne__OH,PJM +38125,40.7827,-81.7829,Wayne__OH,PJM +38126,40.8088,-81.7494,Wayne__OH,PJM +38127,40.9014,-81.7155,Wayne__OH,PJM +38128,40.8415,-81.7459,Wayne__OH,PJM +38129,41.5699,-84.7684,Williams__OH,PJM +38130,41.5112,-84.6274,Williams__OH,PJM +38131,41.5112,-84.6274,Williams__OH,PJM +38132,41.6941,-84.5536,Williams__OH,PJM +38133,41.6941,-84.5536,Williams__OH,PJM +38134,41.6216,-84.6467,Williams__OH,PJM +38135,41.4464,-83.6593,Wood__OH,PJM +38136,41.3982,-83.6969,Wood__OH,PJM +38137,41.4856,-83.5915,Wood__OH,PJM +38138,41.449,-83.6206,Wood__OH,PJM +38139,41.3167,-83.6352,Wood__OH,PJM +38140,41.4359,-83.4634,Wood__OH,PJM +38141,41.4359,-83.4634,Wood__OH,PJM +38142,41.4831,-83.6603,Wood__OH,PJM +38143,41.5261,-83.5564,Wood__OH,PJM +38144,41.537,-83.6018,Wood__OH,PJM +38145,41.537,-83.6018,Wood__OH,PJM +38146,41.4768,-83.557,Wood__OH,PJM +38147,41.4768,-83.557,Wood__OH,PJM +38148,41.3474,-83.8417,Wood__OH,PJM +38149,40.7977,-83.3172,Wyandot__OH,PJM +38150,40.8221,-83.3052,Wyandot__OH,PJM +38151,40.8773,-83.2287,Wyandot__OH,PJM +38152,41.4984,-82.076,Lorain__OH,PJM +38153,41.4984,-82.076,Lorain__OH,PJM +38154,41.4984,-82.076,Lorain__OH,PJM +38155,40.7193,-82.8037,Crawford__OH,PJM +38156,40.7193,-82.8037,Crawford__OH,PJM +38157,40.7193,-82.8037,Crawford__OH,PJM +38158,40.7193,-82.8037,Crawford__OH,PJM +38159,41.4931,-81.7273,Cuyahoga__OH,PJM +38160,41.4931,-81.7273,Cuyahoga__OH,PJM +38161,41.4931,-81.7273,Cuyahoga__OH,PJM +38162,41.4931,-81.7273,Cuyahoga__OH,PJM +38163,41.4931,-81.7273,Cuyahoga__OH,PJM +38164,41.4824,-84.4177,Williams__OH,PJM +38165,41.4824,-84.4177,Williams__OH,PJM +38166,41.4824,-84.4177,Williams__OH,PJM +38167,41.4218,-82.2674,Lorain__OH,PJM +38168,41.4218,-82.2674,Lorain__OH,PJM +38169,41.4218,-82.2674,Lorain__OH,PJM +38170,41.4218,-82.2674,Lorain__OH,PJM +38171,41.4218,-82.2674,Lorain__OH,PJM +38172,41.4218,-82.2674,Lorain__OH,PJM +38173,41.4218,-82.2674,Lorain__OH,PJM +38174,41.4218,-82.2674,Lorain__OH,PJM +38175,41.4218,-82.2674,Lorain__OH,PJM +38176,41.4218,-82.2674,Lorain__OH,PJM +38177,41.4218,-82.2674,Lorain__OH,PJM +38178,40.8918,-84.6125,Van Wert__OH,PJM +38179,40.8918,-84.6125,Van Wert__OH,PJM +38180,41.4923,-82.0216,Lorain__OH,PJM +38181,41.4923,-82.0216,Lorain__OH,PJM +38182,41.4923,-82.0216,Lorain__OH,PJM +38183,41.4923,-82.0216,Lorain__OH,PJM +38184,41.4923,-82.0216,Lorain__OH,PJM +38185,41.4923,-82.0216,Lorain__OH,PJM +38186,41.4923,-82.0216,Lorain__OH,PJM +38187,41.4923,-82.0216,Lorain__OH,PJM +38188,41.3967,-84.1132,Henry__OH,PJM +38189,41.3967,-84.1132,Henry__OH,PJM +38190,41.3967,-84.1132,Henry__OH,PJM +38191,40.7639,-82.5646,Richland__OH,PJM +38192,40.7639,-82.5646,Richland__OH,PJM +38193,40.7639,-82.5646,Richland__OH,PJM +38194,40.7639,-82.5646,Richland__OH,PJM +38195,40.7639,-82.5646,Richland__OH,PJM +38196,40.7639,-82.5646,Richland__OH,PJM +38197,40.7639,-82.5646,Richland__OH,PJM +38198,40.7639,-82.5646,Richland__OH,PJM +38199,40.7639,-82.5646,Richland__OH,PJM +38200,40.9025,-84.7396,Van Wert__OH,PJM +38201,40.9025,-84.7396,Van Wert__OH,PJM +38202,40.9025,-84.7396,Van Wert__OH,PJM +38203,40.9025,-84.7396,Van Wert__OH,PJM +38204,40.9025,-84.7396,Van Wert__OH,PJM +38205,40.9025,-84.7396,Van Wert__OH,PJM +38206,40.9025,-84.7396,Van Wert__OH,PJM +38207,40.9025,-84.7396,Van Wert__OH,PJM +38208,41.3998,-84.0804,Henry__OH,PJM +38209,41.3998,-84.0804,Henry__OH,PJM +38210,41.3998,-84.0804,Henry__OH,PJM +38211,41.3998,-84.0804,Henry__OH,PJM +38212,41.3998,-84.0804,Henry__OH,PJM +38213,41.6117,-83.0991,Ottawa__OH,PJM +38214,41.6117,-83.0991,Ottawa__OH,PJM +38215,41.6117,-83.0991,Ottawa__OH,PJM +38216,41.6117,-83.0991,Ottawa__OH,PJM +38217,41.6117,-83.0991,Ottawa__OH,PJM +38218,41.6117,-83.0991,Ottawa__OH,PJM +38219,41.4215,-84.767,Defiance__OH,PJM +38220,41.4215,-84.767,Defiance__OH,PJM +38221,41.4215,-84.767,Defiance__OH,PJM +38222,41.4215,-84.767,Defiance__OH,PJM +38223,41.4215,-84.767,Defiance__OH,PJM +38224,41.4215,-84.767,Defiance__OH,PJM +38225,41.4215,-84.767,Defiance__OH,PJM +38226,41.4215,-84.767,Defiance__OH,PJM +38227,40.9861,-81.7651,Wayne__OH,PJM +38228,40.9861,-81.7651,Wayne__OH,PJM +38229,40.7486,-82.7906,Crawford__OH,PJM +38230,40.7486,-82.7906,Crawford__OH,PJM +38231,40.7486,-82.7906,Crawford__OH,PJM +38232,40.7486,-82.7906,Crawford__OH,PJM +38233,40.7486,-82.7906,Crawford__OH,PJM +38234,41.6775,-83.4692,Lucas__OH,PJM +38235,41.6775,-83.4692,Lucas__OH,PJM +38236,41.6775,-83.4692,Lucas__OH,PJM +38237,41.6775,-83.4692,Lucas__OH,PJM +38238,41.2526,-82.2322,Lorain__OH,PJM +38239,41.2526,-82.2322,Lorain__OH,PJM +38240,41.6323,-81.4535,Lake__OH,PJM +38241,41.6323,-81.4535,Lake__OH,PJM +38242,41.6323,-81.4535,Lake__OH,PJM +38243,41.4528,-84.5381,Williams__OH,PJM +38244,41.4528,-84.5381,Williams__OH,PJM +38245,41.4528,-84.5381,Williams__OH,PJM +38246,41.4528,-84.5381,Williams__OH,PJM +38247,41.4528,-84.5381,Williams__OH,PJM +38248,41.4983,-81.6527,Cuyahoga__OH,PJM +38249,41.4983,-81.6527,Cuyahoga__OH,PJM +38250,41.4983,-81.6527,Cuyahoga__OH,PJM +38251,41.4983,-81.6527,Cuyahoga__OH,PJM +38252,41.4983,-81.6527,Cuyahoga__OH,PJM +38253,41.4983,-81.6527,Cuyahoga__OH,PJM +38254,41.4983,-81.6527,Cuyahoga__OH,PJM +38255,41.4983,-81.6527,Cuyahoga__OH,PJM +38256,41.4737,-83.4585,Wood__OH,PJM +38257,41.4737,-83.4585,Wood__OH,PJM +38258,41.4737,-83.4585,Wood__OH,PJM +38259,41.4737,-83.4585,Wood__OH,PJM +38260,41.4737,-83.4585,Wood__OH,PJM +38261,41.4737,-83.4585,Wood__OH,PJM +38262,41.4737,-83.4585,Wood__OH,PJM +38263,41.4737,-83.4585,Wood__OH,PJM +38264,41.4737,-83.4585,Wood__OH,PJM +38265,40.8992,-81.766,Wayne__OH,PJM +38266,40.8992,-81.766,Wayne__OH,PJM +38267,41.4398,-84.1023,Henry__OH,PJM +38268,41.4398,-84.1023,Henry__OH,PJM +38269,41.4398,-84.1023,Henry__OH,PJM +38270,41.4398,-84.1023,Henry__OH,PJM +38271,41.4398,-84.1023,Henry__OH,PJM +38272,41.389,-83.6099,Wood__OH,PJM +38273,41.389,-83.6099,Wood__OH,PJM +38274,41.389,-83.6099,Wood__OH,PJM +38275,41.389,-83.6099,Wood__OH,PJM +38276,41.389,-83.6099,Wood__OH,PJM +38277,41.389,-83.6099,Wood__OH,PJM +38278,41.1594,-81.3381,Portage__OH,PJM +38279,41.1594,-81.3381,Portage__OH,PJM +38280,41.1594,-81.3381,Portage__OH,PJM +38281,41.5268,-81.5606,Cuyahoga__OH,PJM +38282,41.5268,-81.5606,Cuyahoga__OH,PJM +38283,41.5268,-81.5606,Cuyahoga__OH,PJM +38284,41.5268,-81.5606,Cuyahoga__OH,PJM +38285,41.3725,-83.6164,Wood__OH,PJM +38286,41.3725,-83.6164,Wood__OH,PJM +38287,41.3725,-83.6164,Wood__OH,PJM +38288,41.3725,-83.6164,Wood__OH,PJM +38289,41.3725,-83.6164,Wood__OH,PJM +38290,41.3725,-83.6164,Wood__OH,PJM +38291,41.3725,-83.6164,Wood__OH,PJM +38292,41.9082,-80.7765,Ashtabula__OH,PJM +38293,41.9082,-80.7765,Ashtabula__OH,PJM +38294,41.9082,-80.7765,Ashtabula__OH,PJM +38295,41.9082,-80.7765,Ashtabula__OH,PJM +38296,41.9082,-80.7765,Ashtabula__OH,PJM +38297,41.8623,-80.7991,Ashtabula__OH,PJM +38298,41.8623,-80.7991,Ashtabula__OH,PJM +38299,41.8623,-80.7991,Ashtabula__OH,PJM +38300,41.8623,-80.7991,Ashtabula__OH,PJM +38301,41.8623,-80.7991,Ashtabula__OH,PJM +38302,41.8623,-80.7991,Ashtabula__OH,PJM +38303,41.8623,-80.7991,Ashtabula__OH,PJM +38304,41.8623,-80.7991,Ashtabula__OH,PJM +38305,41.8623,-80.7991,Ashtabula__OH,PJM +38306,41.7224,-83.4536,Lucas__OH,PJM +38307,41.7224,-83.4536,Lucas__OH,PJM +38308,41.723,-81.238,Lake__OH,PJM +38309,41.723,-81.238,Lake__OH,PJM +38310,41.723,-81.238,Lake__OH,PJM +38311,41.723,-81.238,Lake__OH,PJM +38312,41.723,-81.238,Lake__OH,PJM +38313,41.723,-81.238,Lake__OH,PJM +38314,41.6898,-81.4163,Lake__OH,PJM +38315,41.6898,-81.4163,Lake__OH,PJM +38316,41.6898,-81.4163,Lake__OH,PJM +38317,41.6898,-81.4163,Lake__OH,PJM +38318,41.6898,-81.4163,Lake__OH,PJM +38319,41.6898,-81.4163,Lake__OH,PJM +38320,41.6898,-81.4163,Lake__OH,PJM +38321,41.6898,-81.4163,Lake__OH,PJM +38322,41.6898,-81.4163,Lake__OH,PJM +38323,40.8933,-82.6685,Richland__OH,PJM +38324,40.8933,-82.6685,Richland__OH,PJM +38325,40.8933,-82.6685,Richland__OH,PJM +38326,40.8933,-82.6685,Richland__OH,PJM +38327,40.8933,-82.6685,Richland__OH,PJM +38328,41.396,-84.0959,Henry__OH,PJM +38329,41.396,-84.0959,Henry__OH,PJM +38330,41.396,-84.0959,Henry__OH,PJM +38331,41.396,-84.0959,Henry__OH,PJM +38332,41.396,-84.0959,Henry__OH,PJM +38333,41.405,-82.2858,Lorain__OH,PJM +38334,41.405,-82.2858,Lorain__OH,PJM +38335,41.3075,-84.3137,Defiance__OH,PJM +38336,41.3075,-84.3137,Defiance__OH,PJM +38337,41.3075,-84.3137,Defiance__OH,PJM +38338,41.7696,-81.1502,Lake__OH,PJM +38339,41.7696,-81.1502,Lake__OH,PJM +38340,41.7696,-81.1502,Lake__OH,PJM +38341,41.7696,-81.1502,Lake__OH,PJM +38342,41.7696,-81.1502,Lake__OH,PJM +38343,41.7696,-81.1502,Lake__OH,PJM +38344,41.447,-84.5104,Williams__OH,PJM +38345,41.447,-84.5104,Williams__OH,PJM +38346,41.447,-84.5104,Williams__OH,PJM +38347,41.447,-84.5104,Williams__OH,PJM +38348,41.447,-84.5104,Williams__OH,PJM +38349,41.447,-84.5104,Williams__OH,PJM +38350,41.447,-84.5104,Williams__OH,PJM +38351,41.447,-84.5104,Williams__OH,PJM +38352,41.447,-84.5104,Williams__OH,PJM +38353,41.5886,-84.531,Williams__OH,PJM +38354,41.5886,-84.531,Williams__OH,PJM +38355,41.3996,-83.1682,Sandusky__OH,PJM +38356,41.3996,-83.1682,Sandusky__OH,PJM +38357,41.3996,-83.1682,Sandusky__OH,PJM +38358,41.3996,-83.1682,Sandusky__OH,PJM +38359,41.3996,-83.1682,Sandusky__OH,PJM +38360,41.3996,-83.1682,Sandusky__OH,PJM +38361,41.3996,-83.1682,Sandusky__OH,PJM +38362,41.6859,-83.4586,Lucas__OH,PJM +38363,41.6859,-83.4586,Lucas__OH,PJM +38364,41.6859,-83.4586,Lucas__OH,PJM +38365,41.0558,-81.8663,Medina__OH,PJM +38366,41.0558,-81.8663,Medina__OH,PJM +38367,41.0558,-81.8663,Medina__OH,PJM +38368,41.0558,-81.8663,Medina__OH,PJM +38369,41.0558,-81.8663,Medina__OH,PJM +38370,41.0558,-81.8663,Medina__OH,PJM +38371,41.0558,-81.8663,Medina__OH,PJM +38372,41.5339,-81.6293,Cuyahoga__OH,PJM +38373,41.5339,-81.6293,Cuyahoga__OH,PJM +38374,41.5339,-81.6293,Cuyahoga__OH,PJM +38375,40.8244,-81.7532,Wayne__OH,PJM +38376,40.8244,-81.7532,Wayne__OH,PJM +38377,40.8244,-81.7532,Wayne__OH,PJM +38378,40.8244,-81.7532,Wayne__OH,PJM +38379,41.021,-84.5941,Paulding__OH,PJM +38380,41.021,-84.5941,Paulding__OH,PJM +38381,41.646,-83.454,Lucas__OH,PJM +38382,41.646,-83.454,Lucas__OH,PJM +38383,41.1445,-80.7474,Trumbull__OH,PJM +38384,41.1445,-80.7474,Trumbull__OH,PJM +38385,41.1445,-80.7474,Trumbull__OH,PJM +38386,41.5143,-83.3795,Ottawa__OH,PJM +38387,41.5143,-83.3795,Ottawa__OH,PJM +38388,41.3914,-84.0863,Henry__OH,PJM +38389,41.3914,-84.0863,Henry__OH,PJM +38390,41.3019,-84.3495,Defiance__OH,PJM +38391,41.3019,-84.3495,Defiance__OH,PJM +38392,41.3019,-84.3495,Defiance__OH,PJM +38393,41.3019,-84.3495,Defiance__OH,PJM +38394,41.1696,-80.7846,Trumbull__OH,PJM +38395,41.1696,-80.7846,Trumbull__OH,PJM +38396,41.1696,-80.7846,Trumbull__OH,PJM +38397,41.1696,-80.7846,Trumbull__OH,PJM +38398,41.264,-82.2193,Lorain__OH,PJM +38399,41.264,-82.2193,Lorain__OH,PJM +38400,41.264,-82.2193,Lorain__OH,PJM +38401,41.264,-82.2193,Lorain__OH,PJM +38402,41.264,-82.2193,Lorain__OH,PJM +38403,41.264,-82.2193,Lorain__OH,PJM +38404,40.8728,-83.3074,Wyandot__OH,PJM +38405,40.8728,-83.3074,Wyandot__OH,PJM +38406,40.8728,-83.3074,Wyandot__OH,PJM +38407,40.8728,-83.3074,Wyandot__OH,PJM +38408,40.8728,-83.3074,Wyandot__OH,PJM +38409,40.8728,-83.3074,Wyandot__OH,PJM +38410,41.3538,-83.7232,Wood__OH,PJM +38411,41.3538,-83.7232,Wood__OH,PJM +38412,41.3538,-83.7232,Wood__OH,PJM +38413,41.3538,-83.7232,Wood__OH,PJM +38414,41.3538,-83.7232,Wood__OH,PJM +38415,41.3538,-83.7232,Wood__OH,PJM +38416,41.3972,-83.6196,Wood__OH,PJM +38417,41.3972,-83.6196,Wood__OH,PJM +38418,41.0434,-84.7582,Paulding__OH,PJM +38419,41.0434,-84.7582,Paulding__OH,PJM +38420,41.0434,-84.7582,Paulding__OH,PJM +38421,41.1187,-81.4609,Summit__OH,PJM +38422,41.1187,-81.4609,Summit__OH,PJM +38423,44.503,-83.754,Iosco__MI,LRZ2_7 +38424,44.6815,-83.4009,Alcona__MI,LRZ2_7 +38425,44.775,-83.3227,Alcona__MI,LRZ2_7 +38426,44.8276,-83.6123,Alcona__MI,LRZ2_7 +38427,44.7884,-83.7243,Alcona__MI,LRZ2_7 +38428,44.6373,-84.132,Oscoda__MI,LRZ2_7 +38429,44.7604,-84.0601,Oscoda__MI,LRZ2_7 +38430,44.7604,-84.0601,Oscoda__MI,LRZ2_7 +38431,44.3693,-83.4546,Iosco__MI,LRZ2_7 +38432,44.3693,-83.4546,Iosco__MI,LRZ2_7 +38433,44.3693,-83.4546,Iosco__MI,LRZ2_7 +38434,44.4877,-83.4073,Iosco__MI,LRZ2_7 +38435,44.4748,-83.436,Iosco__MI,LRZ2_7 +38436,44.4748,-83.436,Iosco__MI,LRZ2_7 +38437,44.4748,-83.436,Iosco__MI,LRZ2_7 +38438,44.4748,-83.436,Iosco__MI,LRZ2_7 +38439,44.4748,-83.436,Iosco__MI,LRZ2_7 +38440,44.4748,-83.436,Iosco__MI,LRZ2_7 +38441,46.6441,-86.0685,Alger__MI,LRZ2_7 +38442,46.6441,-86.0685,Alger__MI,LRZ2_7 +38443,46.5811,-87.4673,Marquette__MI,LRZ2_7 +38444,46.5811,-87.4673,Marquette__MI,LRZ2_7 +38445,46.4991,-87.4297,Marquette__MI,LRZ2_7 +38446,46.5304,-87.5106,Marquette__MI,LRZ2_7 +38447,46.5304,-87.5106,Marquette__MI,LRZ2_7 +38448,46.5304,-87.5106,Marquette__MI,LRZ2_7 +38449,46.5304,-87.5106,Marquette__MI,LRZ2_7 +38450,46.5304,-87.5106,Marquette__MI,LRZ2_7 +38451,46.5949,-87.4003,Marquette__MI,LRZ2_7 +38452,46.4152,-86.7085,Alger__MI,LRZ2_7 +38453,46.4152,-86.7085,Alger__MI,LRZ2_7 +38454,46.3491,-86.6585,Alger__MI,LRZ2_7 +38455,45.9355,-86.823,Delta__MI,LRZ2_7 +38456,46.4502,-86.2627,Schoolcraft__MI,LRZ2_7 +38457,46.3382,-87.1728,Marquette__MI,LRZ2_7 +38458,46.2152,-86.9729,Alger__MI,LRZ2_7 +38459,46.2216,-86.6495,Alger__MI,LRZ2_7 +38460,45.1195,-83.4367,Alpena__MI,LRZ2_7 +38461,45.1426,-83.4844,Alpena__MI,LRZ2_7 +38462,45.023,-83.4887,Alpena__MI,LRZ2_7 +38463,45.196,-83.5163,Alpena__MI,LRZ2_7 +38464,45.0587,-83.9593,Montmorency__MI,LRZ2_7 +38465,45.0587,-83.9593,Montmorency__MI,LRZ2_7 +38466,45.0587,-83.9593,Montmorency__MI,LRZ2_7 +38467,44.9977,-83.7422,Alpena__MI,LRZ2_7 +38468,44.9168,-83.4451,Alpena__MI,LRZ2_7 +38469,44.9168,-83.4451,Alpena__MI,LRZ2_7 +38470,44.9168,-83.4451,Alpena__MI,LRZ2_7 +38471,44.9168,-83.4451,Alpena__MI,LRZ2_7 +38472,44.9168,-83.4451,Alpena__MI,LRZ2_7 +38473,44.9168,-83.4451,Alpena__MI,LRZ2_7 +38474,45.2297,-83.6318,Presque Isle__MI,LRZ2_7 +38475,45.2297,-83.6318,Presque Isle__MI,LRZ2_7 +38476,44.8526,-85.2314,Kalkaska__MI,LRZ2_7 +38477,44.9694,-85.188,Antrim__MI,LRZ2_7 +38478,45.2174,-85.0499,Charlevoix__MI,LRZ2_7 +38479,45.2174,-85.0499,Charlevoix__MI,LRZ2_7 +38480,45.2174,-85.0499,Charlevoix__MI,LRZ2_7 +38481,45.1865,-85.0235,Charlevoix__MI,LRZ2_7 +38482,44.9714,-85.3204,Antrim__MI,LRZ2_7 +38483,45.0982,-85.3196,Antrim__MI,LRZ2_7 +38484,45.2964,-85.1767,Charlevoix__MI,LRZ2_7 +38485,45.3142,-85.2883,Charlevoix__MI,LRZ2_7 +38486,45.2784,-85.195,Charlevoix__MI,LRZ2_7 +38487,45.2784,-85.195,Charlevoix__MI,LRZ2_7 +38488,45.0487,-85.0795,Antrim__MI,LRZ2_7 +38489,45.1235,-85.1418,Charlevoix__MI,LRZ2_7 +38490,45.1235,-85.1418,Charlevoix__MI,LRZ2_7 +38491,45.1068,-85.078,Antrim__MI,LRZ2_7 +38492,45.1068,-85.078,Antrim__MI,LRZ2_7 +38493,45.1638,-85.2991,Antrim__MI,LRZ2_7 +38494,44.8758,-85.0036,Antrim__MI,LRZ2_7 +38495,44.8758,-85.0036,Antrim__MI,LRZ2_7 +38496,44.8975,-84.9073,Antrim__MI,LRZ2_7 +38497,44.938,-85.0099,Antrim__MI,LRZ2_7 +38498,44.6924,-85.3822,Grand Traverse__MI,LRZ2_7 +38499,44.8257,-85.4516,Grand Traverse__MI,LRZ2_7 +38500,44.8257,-85.4516,Grand Traverse__MI,LRZ2_7 +38501,44.8117,-85.3625,Grand Traverse__MI,LRZ2_7 +38502,44.8117,-85.3625,Grand Traverse__MI,LRZ2_7 +38503,44.1107,-84.2342,Gladwin__MI,LRZ2_7 +38504,44.0722,-83.633,Arenac__MI,LRZ2_7 +38505,44.0832,-83.7461,Arenac__MI,LRZ2_7 +38506,44.0832,-83.7461,Arenac__MI,LRZ2_7 +38507,43.8465,-83.9287,Bay__MI,LRZ2_7 +38508,43.8465,-83.9287,Bay__MI,LRZ2_7 +38509,43.8052,-83.9636,Bay__MI,LRZ2_7 +38510,43.8052,-83.9636,Bay__MI,LRZ2_7 +38511,43.8838,-84.0562,Bay__MI,LRZ2_7 +38512,43.8838,-84.0562,Bay__MI,LRZ2_7 +38513,43.9581,-83.9212,Arenac__MI,LRZ2_7 +38514,43.9407,-83.9788,Arenac__MI,LRZ2_7 +38515,44.0422,-84.0266,Arenac__MI,LRZ2_7 +38516,44.0422,-84.0266,Arenac__MI,LRZ2_7 +38517,43.9634,-84.0597,Bay__MI,LRZ2_7 +38518,43.9634,-84.0597,Bay__MI,LRZ2_7 +38519,44.2633,-83.5226,Iosco__MI,LRZ2_7 +38520,44.2633,-83.5226,Iosco__MI,LRZ2_7 +38521,44.259,-83.7429,Iosco__MI,LRZ2_7 +38522,44.2863,-83.5798,Iosco__MI,LRZ2_7 +38523,46.7226,-88.5818,Baraga__MI,LRZ2_7 +38524,46.7226,-88.5818,Baraga__MI,LRZ2_7 +38525,46.7231,-88.4918,Baraga__MI,LRZ2_7 +38526,46.7231,-88.4918,Baraga__MI,LRZ2_7 +38527,46.6973,-88.2925,Baraga__MI,LRZ2_7 +38528,46.6973,-88.2925,Baraga__MI,LRZ2_7 +38529,46.6973,-88.2925,Baraga__MI,LRZ2_7 +38530,46.4226,-88.2709,Baraga__MI,LRZ2_7 +38531,46.813,-88.7212,Houghton__MI,LRZ2_7 +38532,46.813,-88.7212,Houghton__MI,LRZ2_7 +38533,43.6361,-84.2273,Midland__MI,LRZ2_7 +38534,43.6487,-83.9986,Bay__MI,LRZ2_7 +38535,43.6224,-83.9587,Bay__MI,LRZ2_7 +38536,43.5235,-83.9495,Bay__MI,LRZ2_7 +38537,43.6406,-83.9348,Bay__MI,LRZ2_7 +38538,43.5922,-83.8475,Bay__MI,LRZ2_7 +38539,43.5071,-83.8326,Saginaw__MI,LRZ2_7 +38540,43.5071,-83.8326,Saginaw__MI,LRZ2_7 +38541,43.5154,-83.8671,Saginaw__MI,LRZ2_7 +38542,43.5452,-83.9106,Bay__MI,LRZ2_7 +38543,43.5452,-83.9106,Bay__MI,LRZ2_7 +38544,43.5036,-83.8852,Saginaw__MI,LRZ2_7 +38545,43.4881,-83.6904,Tuscola__MI,LRZ2_7 +38546,43.4881,-83.6904,Tuscola__MI,LRZ2_7 +38547,43.623,-83.8109,Bay__MI,LRZ2_7 +38548,43.5694,-83.8043,Bay__MI,LRZ2_7 +38549,43.5369,-84.0895,Saginaw__MI,LRZ2_7 +38550,43.6129,-84.1099,Bay__MI,LRZ2_7 +38551,43.5404,-84.1209,Saginaw__MI,LRZ2_7 +38552,43.7607,-84.0091,Bay__MI,LRZ2_7 +38553,43.7607,-84.0091,Bay__MI,LRZ2_7 +38554,43.7231,-84.0341,Bay__MI,LRZ2_7 +38555,43.7231,-84.0341,Bay__MI,LRZ2_7 +38556,43.6802,-84.2508,Midland__MI,LRZ2_7 +38557,43.7846,-84.1906,Midland__MI,LRZ2_7 +38558,43.7846,-84.1906,Midland__MI,LRZ2_7 +38559,43.7846,-84.1906,Midland__MI,LRZ2_7 +38560,43.7705,-84.1756,Midland__MI,LRZ2_7 +38561,43.6655,-84.2386,Midland__MI,LRZ2_7 +38562,43.4251,-83.6811,Tuscola__MI,LRZ2_7 +38563,43.4251,-83.6811,Tuscola__MI,LRZ2_7 +38564,43.8538,-84.2156,Gladwin__MI,LRZ2_7 +38565,43.516,-84.0172,Saginaw__MI,LRZ2_7 +38566,43.4849,-83.9163,Saginaw__MI,LRZ2_7 +38567,43.5014,-83.9387,Saginaw__MI,LRZ2_7 +38568,44.5276,-86.0417,Benzie__MI,LRZ2_7 +38569,44.6927,-85.9973,Benzie__MI,LRZ2_7 +38570,44.6641,-86.1565,Benzie__MI,LRZ2_7 +38571,44.6641,-86.1565,Benzie__MI,LRZ2_7 +38572,44.7282,-86.1599,Benzie__MI,LRZ2_7 +38573,44.6799,-85.811,Grand Traverse__MI,LRZ2_7 +38574,44.6799,-85.811,Grand Traverse__MI,LRZ2_7 +38575,44.5955,-85.7944,Grand Traverse__MI,LRZ2_7 +38576,44.5955,-85.7944,Grand Traverse__MI,LRZ2_7 +38577,44.8699,-85.8852,Leelanau__MI,LRZ2_7 +38578,44.7871,-85.9401,Leelanau__MI,LRZ2_7 +38579,44.4959,-85.8611,Manistee__MI,LRZ2_7 +38580,44.7999,-85.6565,Leelanau__MI,LRZ2_7 +38581,44.7999,-85.6565,Leelanau__MI,LRZ2_7 +38582,44.7999,-85.6565,Leelanau__MI,LRZ2_7 +38583,44.7339,-85.7264,Grand Traverse__MI,LRZ2_7 +38584,44.7339,-85.7264,Grand Traverse__MI,LRZ2_7 +38585,44.8449,-85.6598,Leelanau__MI,LRZ2_7 +38586,44.8449,-85.6598,Leelanau__MI,LRZ2_7 +38587,44.7767,-85.797,Leelanau__MI,LRZ2_7 +38588,44.7767,-85.797,Leelanau__MI,LRZ2_7 +38589,44.7767,-85.797,Leelanau__MI,LRZ2_7 +38590,45.4163,-84.8599,Emmet__MI,LRZ2_7 +38591,45.2357,-84.8269,Charlevoix__MI,LRZ2_7 +38592,45.3148,-84.8715,Emmet__MI,LRZ2_7 +38593,45.3347,-85.0344,Emmet__MI,LRZ2_7 +38594,45.3347,-85.0344,Emmet__MI,LRZ2_7 +38595,45.186,-84.5694,Otsego__MI,LRZ2_7 +38596,45.5747,-84.7107,Cheboygan__MI,LRZ2_7 +38597,45.5152,-84.7921,Emmet__MI,LRZ2_7 +38598,45.3947,-84.786,Emmet__MI,LRZ2_7 +38599,45.3947,-84.786,Emmet__MI,LRZ2_7 +38600,45.4894,-84.4464,Cheboygan__MI,LRZ2_7 +38601,45.6149,-84.5409,Cheboygan__MI,LRZ2_7 +38602,45.6149,-84.5409,Cheboygan__MI,LRZ2_7 +38603,45.4643,-84.4544,Cheboygan__MI,LRZ2_7 +38604,45.4643,-84.4544,Cheboygan__MI,LRZ2_7 +38605,45.4643,-84.4544,Cheboygan__MI,LRZ2_7 +38606,45.322,-84.5804,Cheboygan__MI,LRZ2_7 +38607,45.4301,-84.4998,Cheboygan__MI,LRZ2_7 +38608,45.5301,-84.578,Cheboygan__MI,LRZ2_7 +38609,45.6044,-84.8312,Emmet__MI,LRZ2_7 +38610,45.7882,-84.7768,Emmet__MI,LRZ2_7 +38611,45.2044,-84.2072,Presque Isle__MI,LRZ2_7 +38612,45.3903,-84.2596,Cheboygan__MI,LRZ2_7 +38613,45.3037,-84.3005,Cheboygan__MI,LRZ2_7 +38614,46.4087,-84.7125,Chippewa__MI,LRZ2_7 +38615,45.9593,-84.0188,Chippewa__MI,LRZ2_7 +38616,45.972,-83.5751,Chippewa__MI,LRZ2_7 +38617,46.4433,-85.0536,Chippewa__MI,LRZ2_7 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+60060,30.7318,-93.5849,Beauregard__LA,LRZ8_9_10 +60061,30.7318,-93.5849,Beauregard__LA,LRZ8_9_10 +60062,30.3675,-93.6154,Calcasieu__LA,LRZ8_9_10 +60063,30.3675,-93.6154,Calcasieu__LA,LRZ8_9_10 +60064,32.5911,-92.9887,Claiborne__LA,LRZ8_9_10 +60065,32.614,-92.8101,Lincoln__LA,LRZ8_9_10 +60066,32.614,-92.8101,Lincoln__LA,LRZ8_9_10 +60067,32.4333,-93.1974,Bienville__LA,LRZ8_9_10 +60068,32.224,-92.7899,Bienville__LA,LRZ8_9_10 +60069,32.2784,-92.6899,Jackson__LA,LRZ8_9_10 +60070,32.1844,-92.6971,Jackson__LA,LRZ8_9_10 +60071,32.1844,-92.6971,Jackson__LA,LRZ8_9_10 +60072,32.6549,-93.2951,Webster__LA,LRZ8_9_10 +60073,32.6418,-93.3275,Webster__LA,LRZ8_9_10 +60074,32.6418,-93.3275,Webster__LA,LRZ8_9_10 +60075,32.6418,-93.3275,Webster__LA,LRZ8_9_10 +60076,32.6418,-93.3275,Webster__LA,LRZ8_9_10 +60077,32.6418,-93.3275,Webster__LA,LRZ8_9_10 +60078,32.6418,-93.3275,Webster__LA,LRZ8_9_10 +60079,32.6932,-93.202,Webster__LA,LRZ8_9_10 +60080,32.6932,-93.202,Webster__LA,LRZ8_9_10 +60081,32.2646,-93.3649,Bienville__LA,LRZ8_9_10 +60082,32.219,-93.1936,Bienville__LA,LRZ8_9_10 +60083,32.0389,-92.9469,Natchitoches__LA,LRZ8_9_10 +60084,32.799,-93.5741,Bossier__LA,LRZ8_9_10 +60085,32.7717,-93.6299,Bossier__LA,LRZ8_9_10 +60086,32.7401,-93.7131,Bossier__LA,LRZ8_9_10 +60087,32.7401,-93.7131,Bossier__LA,LRZ8_9_10 +60088,32.613,-93.6891,Bossier__LA,LRZ8_9_10 +60089,32.613,-93.6891,Bossier__LA,LRZ8_9_10 +60090,32.6335,-93.7025,Bossier__LA,LRZ8_9_10 +60091,32.5873,-93.7126,Bossier__LA,LRZ8_9_10 +60092,32.5873,-93.7126,Bossier__LA,LRZ8_9_10 +60093,32.5873,-93.7126,Bossier__LA,LRZ8_9_10 +60094,32.5239,-93.692,Bossier__LA,LRZ8_9_10 +60095,32.5239,-93.692,Bossier__LA,LRZ8_9_10 +60096,32.4126,-93.6257,Bossier__LA,LRZ8_9_10 +60097,32.4126,-93.6257,Bossier__LA,LRZ8_9_10 +60098,32.4601,-93.5906,Bossier__LA,LRZ8_9_10 +60099,32.4601,-93.5906,Bossier__LA,LRZ8_9_10 +60100,32.4601,-93.5906,Bossier__LA,LRZ8_9_10 +60101,32.4601,-93.5906,Bossier__LA,LRZ8_9_10 +60102,32.4601,-93.5906,Bossier__LA,LRZ8_9_10 +60103,32.4781,-93.6316,Bossier__LA,LRZ8_9_10 +60104,32.4781,-93.6316,Bossier__LA,LRZ8_9_10 +60105,32.5043,-93.5999,Bossier__LA,LRZ8_9_10 +60106,32.5043,-93.5999,Bossier__LA,LRZ8_9_10 +60107,32.5127,-93.48,Bossier__LA,LRZ8_9_10 +60108,32.5127,-93.48,Bossier__LA,LRZ8_9_10 +60109,32.4769,-93.5408,Bossier__LA,LRZ8_9_10 +60110,32.4769,-93.5408,Bossier__LA,LRZ8_9_10 +60111,32.4487,-93.511,Bossier__LA,LRZ8_9_10 +60112,32.4496,-93.4552,Bossier__LA,LRZ8_9_10 +60113,32.9708,-93.7073,Bossier__LA,LRZ8_9_10 +60114,32.6042,-93.5491,Bossier__LA,LRZ8_9_10 +60115,32.6042,-93.5491,Bossier__LA,LRZ8_9_10 +60116,32.5686,-93.7627,Caddo__LA,CSWS +60117,32.4808,-93.7615,Caddo__LA,CSWS +60118,32.4477,-93.5596,Bossier__LA,LRZ8_9_10 +60119,32.4477,-93.5596,Bossier__LA,LRZ8_9_10 +60120,32.5077,-93.7658,Caddo__LA,CSWS +60121,32.5077,-93.7658,Caddo__LA,CSWS +60122,32.6327,-93.8373,Caddo__LA,CSWS +60123,32.5951,-93.8167,Caddo__LA,CSWS +60124,32.5993,-93.867,Caddo__LA,CSWS +60125,32.5993,-93.867,Caddo__LA,CSWS +60126,32.5578,-93.8376,Caddo__LA,CSWS +60127,32.8509,-93.448,Webster__LA,LRZ8_9_10 +60128,32.8509,-93.448,Webster__LA,LRZ8_9_10 +60129,33.0037,-93.49,Webster__LA,LRZ8_9_10 +60130,32.2425,-93.8556,De Soto__LA,CSWS +60131,32.2425,-93.8556,De Soto__LA,CSWS +60132,32.2289,-93.9467,Caddo__LA,CSWS +60133,32.2505,-93.9018,Caddo__LA,CSWS +60134,32.7657,-93.9374,Caddo__LA,CSWS +60135,32.3425,-93.6161,Caddo__LA,CSWS +60136,32.3894,-93.6898,Caddo__LA,CSWS +60137,32.3209,-93.6871,Caddo__LA,CSWS +60138,32.3209,-93.6871,Caddo__LA,CSWS +60139,32.3209,-93.6871,Caddo__LA,CSWS +60140,32.4307,-93.7603,Caddo__LA,CSWS +60141,32.4101,-93.8631,Caddo__LA,CSWS +60142,32.3954,-93.828,Caddo__LA,CSWS +60143,32.5235,-93.8057,Caddo__LA,CSWS +60144,32.2339,-93.6742,De Soto__LA,CSWS +60145,32.2339,-93.6742,De Soto__LA,CSWS +60146,32.2335,-93.6375,De Soto__LA,CSWS +60147,32.2755,-93.558,Caddo__LA,CSWS +60148,32.3817,-93.7914,Caddo__LA,CSWS +60149,32.3322,-93.7322,Caddo__LA,CSWS +60150,32.4463,-93.8653,Caddo__LA,CSWS +60151,32.4437,-93.8015,Caddo__LA,CSWS +60152,32.53,-93.9974,Caddo__LA,CSWS +60153,32.5144,-93.8987,Caddo__LA,CSWS +60154,32.4377,-93.9485,Caddo__LA,CSWS +60155,32.4377,-93.9485,Caddo__LA,CSWS +60156,32.4377,-93.9485,Caddo__LA,CSWS +60157,32.3928,-93.8949,Caddo__LA,CSWS +60158,32.3452,-93.9035,Caddo__LA,CSWS +60159,32.8597,-93.973,Caddo__LA,CSWS +60160,32.8783,-93.8951,Caddo__LA,CSWS +60161,32.8783,-93.8951,Caddo__LA,CSWS +60162,30.032,-93.0105,Cameron__LA,LRZ8_9_10 +60163,30.032,-93.0105,Cameron__LA,LRZ8_9_10 +60164,30.032,-93.0105,Cameron__LA,LRZ8_9_10 +60165,30.032,-93.0105,Cameron__LA,LRZ8_9_10 +60166,30.032,-93.0105,Cameron__LA,LRZ8_9_10 +60167,30.032,-93.0105,Cameron__LA,LRZ8_9_10 +60168,30.2365,-93.0739,Calcasieu__LA,LRZ8_9_10 +60169,30.3195,-92.959,Jefferson Davis__LA,LRZ8_9_10 +60170,30.3195,-92.959,Jefferson Davis__LA,LRZ8_9_10 +60171,30.1417,-93.1749,Calcasieu__LA,LRZ8_9_10 +60172,30.1417,-93.1749,Calcasieu__LA,LRZ8_9_10 +60173,30.2205,-93.2213,Calcasieu__LA,LRZ8_9_10 +60174,30.2332,-93.1842,Calcasieu__LA,LRZ8_9_10 +60175,30.2519,-93.2681,Calcasieu__LA,LRZ8_9_10 +60176,30.2702,-93.3064,Calcasieu__LA,LRZ8_9_10 +60177,30.0975,-93.3247,Calcasieu__LA,LRZ8_9_10 +60178,30.1984,-93.2988,Calcasieu__LA,LRZ8_9_10 +60179,30.1524,-93.2767,Calcasieu__LA,LRZ8_9_10 +60180,30.1524,-93.2767,Calcasieu__LA,LRZ8_9_10 +60181,30.0234,-93.2139,Cameron__LA,LRZ8_9_10 +60182,30.0234,-93.2139,Cameron__LA,LRZ8_9_10 +60183,30.051,-93.2071,Cameron__LA,LRZ8_9_10 +60184,30.051,-93.2071,Cameron__LA,LRZ8_9_10 +60185,30.0611,-93.1839,Calcasieu__LA,LRZ8_9_10 +60186,30.0963,-93.2193,Calcasieu__LA,LRZ8_9_10 +60187,30.3558,-93.1896,Calcasieu__LA,LRZ8_9_10 +60188,30.3558,-93.1896,Calcasieu__LA,LRZ8_9_10 +60189,30.3662,-93.2771,Calcasieu__LA,LRZ8_9_10 +60190,30.2551,-93.199,Calcasieu__LA,LRZ8_9_10 +60191,30.2551,-93.199,Calcasieu__LA,LRZ8_9_10 +60192,30.1981,-93.2091,Calcasieu__LA,LRZ8_9_10 +60193,30.1981,-93.2091,Calcasieu__LA,LRZ8_9_10 +60194,30.1735,-93.1669,Calcasieu__LA,LRZ8_9_10 +60195,30.2763,-93.3483,Calcasieu__LA,LRZ8_9_10 +60196,30.2667,-93.4463,Calcasieu__LA,LRZ8_9_10 +60197,30.2667,-93.4463,Calcasieu__LA,LRZ8_9_10 +60198,30.2667,-93.4463,Calcasieu__LA,LRZ8_9_10 +60199,30.2667,-93.4463,Calcasieu__LA,LRZ8_9_10 +60200,30.2667,-93.4463,Calcasieu__LA,LRZ8_9_10 +60201,30.2667,-93.4463,Calcasieu__LA,LRZ8_9_10 +60202,30.2947,-93.4212,Calcasieu__LA,LRZ8_9_10 +60203,30.2947,-93.4212,Calcasieu__LA,LRZ8_9_10 +60204,30.3295,-93.3227,Calcasieu__LA,LRZ8_9_10 +60205,30.1336,-93.3794,Calcasieu__LA,LRZ8_9_10 +60206,30.1113,-93.4377,Calcasieu__LA,LRZ8_9_10 +60207,30.0333,-93.4313,Cameron__LA,LRZ8_9_10 +60208,30.0333,-93.4313,Cameron__LA,LRZ8_9_10 +60209,30.2261,-93.5636,Calcasieu__LA,LRZ8_9_10 +60210,30.1127,-93.5998,Calcasieu__LA,LRZ8_9_10 +60211,32.1632,-92.1432,Caldwell__LA,LRZ8_9_10 +60212,32.182,-92.0373,Caldwell__LA,LRZ8_9_10 +60213,32.065,-92.0889,Caldwell__LA,LRZ8_9_10 +60214,32.065,-92.0889,Caldwell__LA,LRZ8_9_10 +60215,31.9872,-92.2109,Caldwell__LA,LRZ8_9_10 +60216,31.8883,-92.2334,LaSalle__LA,LRZ8_9_10 +60217,29.8281,-93.5584,Cameron__LA,LRZ8_9_10 +60218,30.0132,-92.5605,Vermilion__LA,LRZ8_9_10 +60219,30.0132,-92.5605,Vermilion__LA,LRZ8_9_10 +60220,30.0062,-92.8169,Cameron__LA,LRZ8_9_10 +60221,31.7822,-91.811,Catahoula__LA,LRZ8_9_10 +60222,31.5269,-91.8729,Catahoula__LA,LRZ8_9_10 +60223,32.7636,-92.6729,Union__LA,LRZ8_9_10 +60224,32.9842,-93.0698,Claiborne__LA,LRZ8_9_10 +60225,32.7035,-92.9606,Claiborne__LA,LRZ8_9_10 +60226,32.7809,-93.0197,Claiborne__LA,LRZ8_9_10 +60227,32.6843,-93.0295,Claiborne__LA,LRZ8_9_10 +60228,31.6059,-91.5191,Concordia__LA,LRZ8_9_10 +60229,31.6059,-91.5191,Concordia__LA,LRZ8_9_10 +60230,31.6059,-91.5191,Concordia__LA,LRZ8_9_10 +60231,31.6676,-91.5552,Concordia__LA,LRZ8_9_10 +60232,31.6123,-91.5882,Concordia__LA,LRZ8_9_10 +60233,31.6123,-91.5882,Concordia__LA,LRZ8_9_10 +60234,31.6123,-91.5882,Concordia__LA,LRZ8_9_10 +60235,31.2988,-91.5966,Concordia__LA,LRZ8_9_10 +60236,31.2988,-91.5966,Concordia__LA,LRZ8_9_10 +60237,31.8836,-93.6181,De Soto__LA,CSWS +60238,32.0609,-93.9674,De Soto__LA,CSWS +60239,32.0362,-93.6618,De Soto__LA,CSWS +60240,32.0362,-93.6618,De Soto__LA,CSWS +60241,32.0426,-93.6028,De Soto__LA,CSWS +60242,32.0426,-93.6028,De Soto__LA,CSWS +60243,32.2077,-93.7802,De Soto__LA,CSWS +60244,30.5512,-91.1171,East Baton Rouge__LA,LRZ8_9_10 +60245,30.673,-91.1872,East Baton Rouge__LA,LRZ8_9_10 +60246,30.5572,-91.1698,East Baton Rouge__LA,LRZ8_9_10 +60247,30.5572,-91.1698,East Baton Rouge__LA,LRZ8_9_10 +60248,30.5572,-91.1698,East Baton Rouge__LA,LRZ8_9_10 +60249,30.5572,-91.1698,East Baton Rouge__LA,LRZ8_9_10 +60250,30.5572,-91.1698,East Baton Rouge__LA,LRZ8_9_10 +60251,30.5572,-91.1698,East Baton Rouge__LA,LRZ8_9_10 +60252,30.5062,-91.2508,West Baton Rouge__LA,LRZ8_9_10 +60253,30.5062,-91.2508,West Baton Rouge__LA,LRZ8_9_10 +60254,30.5062,-91.2508,West Baton Rouge__LA,LRZ8_9_10 +60255,30.3029,-91.2814,Iberville__LA,LRZ8_9_10 +60256,30.5491,-91.2208,East Baton Rouge__LA,LRZ8_9_10 +60257,30.5491,-91.2208,East Baton Rouge__LA,LRZ8_9_10 +60258,30.518,-91.2262,East Baton Rouge__LA,LRZ8_9_10 +60259,30.518,-91.2262,East Baton Rouge__LA,LRZ8_9_10 +60260,30.4705,-91.0782,East Baton Rouge__LA,LRZ8_9_10 +60261,30.5267,-91.1893,East Baton Rouge__LA,LRZ8_9_10 +60262,30.4677,-91.1912,East Baton Rouge__LA,LRZ8_9_10 +60263,30.4773,-91.0542,East Baton Rouge__LA,LRZ8_9_10 +60264,30.4183,-91.1528,East Baton Rouge__LA,LRZ8_9_10 +60265,30.4183,-91.1528,East Baton Rouge__LA,LRZ8_9_10 +60266,30.5737,-91.2615,East Baton Rouge__LA,LRZ8_9_10 +60267,30.5737,-91.2615,East Baton Rouge__LA,LRZ8_9_10 +60268,30.358,-91.0533,East Baton Rouge__LA,LRZ8_9_10 +60269,30.4026,-91.1985,East Baton Rouge__LA,LRZ8_9_10 +60270,30.4278,-91.1327,East Baton Rouge__LA,LRZ8_9_10 +60271,30.4278,-91.1327,East Baton Rouge__LA,LRZ8_9_10 +60272,30.3823,-91.142,East Baton Rouge__LA,LRZ8_9_10 +60273,30.4274,-91.011,East Baton Rouge__LA,LRZ8_9_10 +60274,30.4274,-91.011,East Baton Rouge__LA,LRZ8_9_10 +60275,30.3573,-91.1452,East Baton Rouge__LA,LRZ8_9_10 +60276,30.3573,-91.1452,East Baton Rouge__LA,LRZ8_9_10 +60277,30.239,-91.1062,Iberville__LA,LRZ8_9_10 +60278,30.239,-91.1062,Iberville__LA,LRZ8_9_10 +60279,30.2945,-91.0569,Iberville__LA,LRZ8_9_10 +60280,30.2945,-91.0569,Iberville__LA,LRZ8_9_10 +60281,30.2923,-91.1416,Iberville__LA,LRZ8_9_10 +60282,30.2516,-90.9697,Ascension__LA,LRZ8_9_10 +60283,30.5287,-91.0892,East Baton Rouge__LA,LRZ8_9_10 +60284,30.5287,-91.0892,East Baton Rouge__LA,LRZ8_9_10 +60285,30.3908,-91.1153,East Baton Rouge__LA,LRZ8_9_10 +60286,30.3908,-91.1153,East Baton Rouge__LA,LRZ8_9_10 +60287,30.3586,-91.0896,East Baton Rouge__LA,LRZ8_9_10 +60288,30.4514,-91.0709,East Baton Rouge__LA,LRZ8_9_10 +60289,30.4514,-91.0709,East Baton Rouge__LA,LRZ8_9_10 +60290,30.4995,-91.0389,East Baton Rouge__LA,LRZ8_9_10 +60291,30.4995,-91.0389,East Baton Rouge__LA,LRZ8_9_10 +60292,30.4505,-91.0331,East Baton Rouge__LA,LRZ8_9_10 +60293,30.4505,-91.0331,East Baton Rouge__LA,LRZ8_9_10 +60294,30.4586,-90.9908,East Baton Rouge__LA,LRZ8_9_10 +60295,30.4586,-90.9908,East Baton Rouge__LA,LRZ8_9_10 +60296,30.4586,-90.9908,East Baton Rouge__LA,LRZ8_9_10 +60297,30.4334,-90.9485,Livingston__LA,LRZ8_9_10 +60298,30.3465,-90.9316,East Baton Rouge__LA,LRZ8_9_10 +60299,30.3831,-90.9358,Livingston__LA,LRZ8_9_10 +60300,30.5404,-90.9837,East Baton Rouge__LA,LRZ8_9_10 +60301,30.5404,-90.9837,East Baton Rouge__LA,LRZ8_9_10 +60302,30.3194,-91.1682,Iberville__LA,LRZ8_9_10 +60303,30.3194,-91.1682,Iberville__LA,LRZ8_9_10 +60304,30.3616,-91.2393,East Baton Rouge__LA,LRZ8_9_10 +60305,30.2999,-91.2383,Iberville__LA,LRZ8_9_10 +60306,30.3761,-91.3159,West Baton Rouge__LA,LRZ8_9_10 +60307,30.8213,-91.0811,East Feliciana__LA,LRZ8_9_10 +60308,30.8213,-91.0811,East Feliciana__LA,LRZ8_9_10 +60309,30.8282,-90.9369,East Feliciana__LA,LRZ8_9_10 +60310,30.5696,-90.8802,Livingston__LA,LRZ8_9_10 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+3008088,31.1803,-96.4866,Robertson__TX,ERCOT +3008089,32.4184,-95.2131,Smith__TX,CSWS +3008090,31.6067,-95.5833,Anderson__TX,ERCOT +3008091,31.8935,-96.4337,Navarro__TX,ERCOT +3008092,31.5573,-95.8637,Leon__TX,ERCOT +3008093,33.242,-94.8578,Titus__TX,ERCOT +3008094,30.5614,-96.2726,Brazos__TX,ERCOT +3008095,30.5614,-96.2726,Brazos__TX,ERCOT +3008096,32.715,-95.8545,Van Zandt__TX,ERCOT +3008097,31.8321,-94.9006,Nacogdoches__TX,ERCOT +3008098,31.8321,-94.9006,Nacogdoches__TX,ERCOT +3008099,31.8321,-94.9006,Nacogdoches__TX,ERCOT +3008100,32.3015,-95.178,Smith__TX,CSWS +3008101,31.613,-95.0621,Cherokee__TX,ERCOT +3008102,31.0031,-96.689,Robertson__TX,ERCOT +3008103,31.3295,-96.1528,Leon__TX,ERCOT +3008104,30.3693,-96.0548,Grimes__TX,ERCOT +3008105,33.3349,-95.1615,Franklin__TX,ERCOT +3008106,33.3349,-95.1615,Franklin__TX,ERCOT +3008107,33.0244,-95.1971,Franklin__TX,ERCOT +3008108,32.7033,-95.9947,Van Zandt__TX,ERCOT +3008109,32.0943,-95.906,Henderson__TX,ERCOT +3008110,32.9893,-95.9129,Hunt__TX,ERCOT +3008111,31.3017,-94.6414,Angelina__TX,ERCOT +3008112,31.9398,-94.9898,Cherokee__TX,ERCOT +3008113,31.9398,-94.9898,Cherokee__TX,ERCOT +3008114,31.9398,-94.9898,Cherokee__TX,ERCOT +3008115,31.9398,-94.9898,Cherokee__TX,ERCOT +3008116,31.9398,-94.9898,Cherokee__TX,ERCOT +3008117,31.9398,-94.9898,Cherokee__TX,ERCOT +3008118,31.1889,-95.2557,Houston__TX,ERCOT +3008119,31.9254,-94.704,Rusk__TX,ERCOT +3008120,30.7977,-96.3121,Brazos__TX,ERCOT +3008121,31.9451,-95.257,Cherokee__TX,ERCOT +3008122,30.743,-96.5484,Robertson__TX,ERCOT +3008123,32.1275,-96.0142,Henderson__TX,ERCOT +3008124,33.0981,-95.8032,Hopkins__TX,ERCOT +3008125,31.5091,-94.5272,Nacogdoches__TX,ERCOT +3008126,33.0917,-95.0417,Titus__TX,ERCOT +3008127,33.0917,-95.0417,Titus__TX,ERCOT +3008128,33.0917,-95.0417,Titus__TX,ERCOT +3008129,33.0917,-95.0417,Titus__TX,ERCOT +3008130,33.0917,-95.0417,Titus__TX,ERCOT +3008131,33.0917,-95.0417,Titus__TX,ERCOT +3008132,31.4789,-96.2298,Freestone__TX,ERCOT +3008133,32.2351,-95.321,Smith__TX,CSWS +3008134,32.2351,-95.321,Smith__TX,CSWS +3008135,32.3624,-95.3153,Smith__TX,CSWS +3008136,32.9251,-95.5682,Wood__TX,CSWS +3008137,31.3908,-95.1267,Houston__TX,ERCOT +3008138,32.3626,-95.0867,Smith__TX,CSWS +3008139,30.6091,-96.326,Brazos__TX,ERCOT +3008140,30.6091,-96.326,Brazos__TX,ERCOT +3008141,30.8719,-96.5269,Robertson__TX,ERCOT +3008142,33.1765,-95.3586,Hopkins__TX,ERCOT +3008143,30.7261,-96.0964,Grimes__TX,ERCOT +3008144,31.7652,-96.3299,Freestone__TX,ERCOT +3008145,33.0142,-95.4609,Hopkins__TX,ERCOT +3008146,32.2394,-94.7283,Rusk__TX,ERCOT +3008147,32.1245,-96.1013,Henderson__TX,ERCOT +3008148,32.1245,-96.1013,Henderson__TX,ERCOT +3008149,32.1245,-96.1013,Henderson__TX,ERCOT +3008150,31.1384,-94.3752,Angelina__TX,ERCOT +3008151,31.4174,-95.4817,Houston__TX,ERCOT +3008152,30.6474,-96.3723,Brazos__TX,ERCOT +3008153,32.5181,-95.8889,Van Zandt__TX,ERCOT +3008154,32.4696,-95.3079,Smith__TX,CSWS +3008155,31.0919,-96.695,Robertson__TX,ERCOT +3008156,31.0919,-96.695,Robertson__TX,ERCOT +3008157,31.0919,-96.695,Robertson__TX,ERCOT +3008158,30.7217,-96.4608,Brazos__TX,ERCOT +3008159,30.7217,-96.4608,Brazos__TX,ERCOT +3008160,30.7217,-96.4608,Brazos__TX,ERCOT From d6214d142e3f6b2576d7a348bdbbc25853e6ce67 Mon Sep 17 00:00:00 2001 From: BainanXia Date: Thu, 8 Jul 2021 17:21:45 -0700 Subject: [PATCH 27/61] feat: add manual fix for county name mismatch and assign BA based on nearest neighbor --- prereise/gather/demanddata/eia/map_ba.py | 32 ++++++++++++++++++++---- 1 file changed, 27 insertions(+), 5 deletions(-) diff --git a/prereise/gather/demanddata/eia/map_ba.py b/prereise/gather/demanddata/eia/map_ba.py index 60d45362e..8bed8bec4 100644 --- a/prereise/gather/demanddata/eia/map_ba.py +++ b/prereise/gather/demanddata/eia/map_ba.py @@ -4,6 +4,7 @@ import pandas as pd import requests +from powersimdata.utility.distance import find_closest_neighbor from tqdm import tqdm import prereise @@ -111,10 +112,21 @@ def map_buses_to_ba(bus_df): lat and long of buses. :return: (*tuple*) -- the first entry is the input data frame with two columns, "County" and "BA", added for each bus and the second entry is the list of bus - indices that no BA matches. + indices that no county matches based on Census API (counties of such buses are + assigned based on its nearest neighbour). """ - bus_ba_map, _ = map_buses_to_county(bus_df) + bus_ba_map, bus_no_county_match = map_buses_to_county(bus_df) + # hard coded fix for county name mismatch between the returns from census API and + # BA_County_map.json + bus_ba_map.County.replace( + { + "Danville City__VA": "Danville__VA", + "Harrisonburg City__VA": "Harrisonburg__VA", + "Franklin City__VA": "Franklin__VA", + }, + inplace=True, + ) # read json file for BA_County Map filepath = os.path.join( @@ -129,7 +141,17 @@ def map_buses_to_ba(bus_df): county_ba_map = { value: key for key in ba_county_map for value in ba_county_map[key] } - bus_ba_map["BA"] = bus_ba_map["County"].map(county_ba_map) - bus_no_ba_match = list(bus_ba_map.query("BA.isna()").index) - return bus_ba_map, bus_no_ba_match + bus_ba_map["BA"] = bus_ba_map["County"].map(county_ba_map) + # assign BA to buses without county assigned based on the nearest neighbor + neighbor = bus_ba_map.query("~County.isna()") + for bus_id in bus_no_county_match: + if neighbor.empty: + print("No reference bus has BA assigned!") + break + ind = find_closest_neighbor( + (bus_ba_map.loc[bus_id, "lon"], bus_ba_map.loc[bus_id, "lat"]), + neighbor[["lon", "lat"]].values.tolist(), + ) + bus_ba_map.loc[bus_id, "BA"] = neighbor.iloc[ind]["BA"] + return bus_ba_map, bus_no_county_match From fe2631a69a2042e5c8aca43c365998f9f955524c Mon Sep 17 00:00:00 2001 From: BainanXia Date: Thu, 8 Jul 2021 17:22:29 -0700 Subject: [PATCH 28/61] fix: update test to reflect nearest neighbor logic --- prereise/gather/demanddata/eia/tests/test_map_ba.py | 7 +++---- 1 file changed, 3 insertions(+), 4 deletions(-) diff --git a/prereise/gather/demanddata/eia/tests/test_map_ba.py b/prereise/gather/demanddata/eia/tests/test_map_ba.py index 8560b27e0..0c6d76657 100644 --- a/prereise/gather/demanddata/eia/tests/test_map_ba.py +++ b/prereise/gather/demanddata/eia/tests/test_map_ba.py @@ -1,4 +1,3 @@ -import numpy as np import pandas as pd from pandas.testing import assert_series_equal @@ -90,7 +89,7 @@ def test_map_buses_to_ba(): }, index=["CA", "Texas", "Beijing"], ) - expected_res = ["LDWP", "ERCOT", np.nan] - bus_ba, bus_no_ba_match = map_buses_to_ba(bus_df) + expected_res = ["LDWP", "ERCOT", "LDWP"] + bus_ba, bus_no_county_match = map_buses_to_ba(bus_df) assert bus_ba["BA"].tolist() == expected_res - assert bus_no_ba_match == ["Beijing"] + assert bus_no_county_match == ["Beijing"] From a490859e0bd491e762391a8fd0935aa705398fef Mon Sep 17 00:00:00 2001 From: George Tong Date: Thu, 15 Jul 2021 11:12:28 -0700 Subject: [PATCH 29/61] feat: add stubs for demand and hydro data cli (#190) --- prereise/cli/data_sources/__init__.py | 4 ++++ prereise/cli/data_sources/data_source.py | 24 +++++++++++++++++++ prereise/cli/data_sources/demand_data.py | 11 +++++++++ prereise/cli/data_sources/exceptions.py | 2 ++ prereise/cli/data_sources/hydro_data.py | 11 +++++++++ .../data_sources/tests/test_demand_data.py | 9 +++++++ .../cli/data_sources/tests/test_hydro_data.py | 9 +++++++ 7 files changed, 70 insertions(+) create mode 100644 prereise/cli/data_sources/demand_data.py create mode 100644 prereise/cli/data_sources/exceptions.py create mode 100644 prereise/cli/data_sources/hydro_data.py create mode 100644 prereise/cli/data_sources/tests/test_demand_data.py create mode 100644 prereise/cli/data_sources/tests/test_hydro_data.py diff --git a/prereise/cli/data_sources/__init__.py b/prereise/cli/data_sources/__init__.py index 3928779b3..1d281e2a5 100644 --- a/prereise/cli/data_sources/__init__.py +++ b/prereise/cli/data_sources/__init__.py @@ -1,3 +1,5 @@ +from prereise.cli.data_sources.demand_data import DemandData +from prereise.cli.data_sources.hydro_data import HydroData from prereise.cli.data_sources.solar_data import ( SolarDataGriddedAtmospheric, SolarDataNationalSolarRadiationDatabase, @@ -14,4 +16,6 @@ def get_data_sources_list(): WindDataRapidRefresh(), SolarDataGriddedAtmospheric(), SolarDataNationalSolarRadiationDatabase(), + DemandData(), + HydroData(), ] diff --git a/prereise/cli/data_sources/data_source.py b/prereise/cli/data_sources/data_source.py index 0c2cd713a..cb918a1e8 100644 --- a/prereise/cli/data_sources/data_source.py +++ b/prereise/cli/data_sources/data_source.py @@ -1,5 +1,7 @@ from abc import ABCMeta, abstractmethod +from prereise.cli.data_sources.exceptions import CommandNotSupportedError + class DataSource(metaclass=ABCMeta): """Abstract class that defines a strict interface @@ -45,3 +47,25 @@ def extract(self): the appropriate data and saves it somewhere. """ pass + + +class NotSupportedDataSource(DataSource): + @property + def command_help(self): + """See :py:func:`prereise.cli.data_sources.data_source.DataSource.command_help` + + :return: (*str*) -- help messsage + """ + return "Currently unsupported, please see documentation to see how to download" + + @property + def extract_arguments(self): + """See :py:func:`prereise.cli.data_sources.data_source.DataSource.extract_arguments` + + :return: (*list*) -- list of arguments to pass into argparse + """ + return [] + + def extract(self, **kwargs): + """See :py:func:`prereise.cli.data_sources.data_source.DataSource.extract`""" + raise CommandNotSupportedError() diff --git a/prereise/cli/data_sources/demand_data.py b/prereise/cli/data_sources/demand_data.py new file mode 100644 index 000000000..c5562b013 --- /dev/null +++ b/prereise/cli/data_sources/demand_data.py @@ -0,0 +1,11 @@ +from prereise.cli.data_sources.data_source import NotSupportedDataSource + + +class DemandData(NotSupportedDataSource): + @property + def command_name(self): + """See :py:func:`prereise.cli.data_sources.data_source.DataSource.command_name` + + :return: (*str*) -- command name + """ + return "demand_data" diff --git a/prereise/cli/data_sources/exceptions.py b/prereise/cli/data_sources/exceptions.py new file mode 100644 index 000000000..05297f548 --- /dev/null +++ b/prereise/cli/data_sources/exceptions.py @@ -0,0 +1,2 @@ +class CommandNotSupportedError(Exception): + pass diff --git a/prereise/cli/data_sources/hydro_data.py b/prereise/cli/data_sources/hydro_data.py new file mode 100644 index 000000000..c5d185cf5 --- /dev/null +++ b/prereise/cli/data_sources/hydro_data.py @@ -0,0 +1,11 @@ +from prereise.cli.data_sources.data_source import NotSupportedDataSource + + +class HydroData(NotSupportedDataSource): + @property + def command_name(self): + """See :py:func:`prereise.cli.data_sources.data_source.DataSource.command_name` + + :return: (*str*) -- command name + """ + return "hydro_data" diff --git a/prereise/cli/data_sources/tests/test_demand_data.py b/prereise/cli/data_sources/tests/test_demand_data.py new file mode 100644 index 000000000..0dccda502 --- /dev/null +++ b/prereise/cli/data_sources/tests/test_demand_data.py @@ -0,0 +1,9 @@ +import pytest + +from prereise.cli.data_sources.demand_data import DemandData +from prereise.cli.data_sources.exceptions import CommandNotSupportedError + + +def test_demand_data_happy_path(): + with pytest.raises(CommandNotSupportedError): + DemandData().extract() diff --git a/prereise/cli/data_sources/tests/test_hydro_data.py b/prereise/cli/data_sources/tests/test_hydro_data.py new file mode 100644 index 000000000..470147693 --- /dev/null +++ b/prereise/cli/data_sources/tests/test_hydro_data.py @@ -0,0 +1,9 @@ +import pytest + +from prereise.cli.data_sources.exceptions import CommandNotSupportedError +from prereise.cli.data_sources.hydro_data import HydroData + + +def test_hydro_data_happy_path(): + with pytest.raises(CommandNotSupportedError): + HydroData().extract() From f2dc3874df5e4b8b600ae0e0d52f6c34ebae9049 Mon Sep 17 00:00:00 2001 From: George Tong Date: Tue, 20 Jul 2021 08:54:01 -0700 Subject: [PATCH 30/61] fix: add imputation of missing wind data for cli (#189) --- .../cli/data_sources/tests/test_wind_data.py | 10 ++++++++-- prereise/cli/data_sources/wind_data.py | 16 ++++++++++++++-- 2 files changed, 22 insertions(+), 4 deletions(-) diff --git a/prereise/cli/data_sources/tests/test_wind_data.py b/prereise/cli/data_sources/tests/test_wind_data.py index eaf8ed273..aa07d0030 100644 --- a/prereise/cli/data_sources/tests/test_wind_data.py +++ b/prereise/cli/data_sources/tests/test_wind_data.py @@ -11,6 +11,8 @@ ) from prereise.cli.data_sources.wind_data import WindDataRapidRefresh +NO_IMPUTE = False + @pytest.fixture def wind_data_object(): @@ -25,6 +27,7 @@ def test_winddata_end_date_before_start_date(wind_data_object): STRING_DATE_2021_5_1, CURRENT_DIRECTORY_FILEPATH, VALID_GRID_MODEL, + NO_IMPUTE, ) @@ -43,6 +46,7 @@ def test_winddata_happy_path(grid, rap, wind_data_object): STRING_DATE_2021_12_1, CURRENT_DIRECTORY_FILEPATH, VALID_GRID_MODEL, + NO_IMPUTE, ) rap.retrieve_data.assert_called_with( wind_farms, start_date=STRING_DATE_2021_5_1, end_date=STRING_DATE_2021_12_1 @@ -53,7 +57,8 @@ def test_winddata_happy_path(grid, rap, wind_data_object): @patch("prereise.cli.data_sources.wind_data.rap") @patch("prereise.cli.data_sources.wind_data.Grid") @patch("prereise.cli.data_sources.wind_data.logging") -def test_winddata_missing_files(logging, grid, rap, wind_data_object): +@patch("prereise.cli.data_sources.wind_data.impute") +def test_winddata_missing_files(impute, logging, grid, rap, wind_data_object): grid_mock = MagicMock() wind_farms = MagicMock() grid_mock.plant.groupby.return_value.get_group.return_value = wind_farms @@ -66,9 +71,10 @@ def test_winddata_missing_files(logging, grid, rap, wind_data_object): STRING_DATE_2021_12_1, CURRENT_DIRECTORY_FILEPATH, VALID_GRID_MODEL, + NO_IMPUTE, ) rap.retrieve_data.assert_called_with( wind_farms, start_date=STRING_DATE_2021_5_1, end_date=STRING_DATE_2021_12_1 ) data.to_pickle.assert_called_with(CURRENT_DIRECTORY_FILEPATH) - logging.warning.assert_called_with("There are 2 files missing") + impute.gaussian.assert_called_with(data, wind_farms, inplace=True) diff --git a/prereise/cli/data_sources/wind_data.py b/prereise/cli/data_sources/wind_data.py index f3465174f..87699772b 100644 --- a/prereise/cli/data_sources/wind_data.py +++ b/prereise/cli/data_sources/wind_data.py @@ -14,7 +14,7 @@ ) from prereise.cli.data_sources.data_source import DataSource from prereise.cli.helpers import validate_date, validate_file_path -from prereise.gather.winddata.rap import rap +from prereise.gather.winddata.rap import impute, rap class WindDataRapidRefresh(DataSource): @@ -73,9 +73,16 @@ def extract_arguments(self): "choices": list(Grid.SUPPORTED_MODELS), "help": GRID_MODEL_HELP_STRING, }, + { + "command_flags": ["--no_impute", "-ni"], + "action": "store_true", + "help": "Flag used to avoid naive gaussian imputing of missing data", + }, ] - def extract(self, region, start_date, end_date, file_path, grid_model, **kwargs): + def extract( + self, region, start_date, end_date, file_path, grid_model, no_impute, **kwargs + ): """See :py:func:`prereise.cli.data_sources.data_source.DataSource.extract` :param list region: list of regions to download wind farm data for @@ -84,6 +91,7 @@ def extract(self, region, start_date, end_date, file_path, grid_model, **kwargs) :param str file_path: file location on local filesystem on where to store the data :param str grid_model: .mat file path for a grid model or a string supported by `powersimdata.input.grid.Grid.SUPPORTED_MODELS` + :param bool no_impute: flag used to avoid naive gaussian imputing of missing data """ assert datetime.strptime(start_date, DATE_FMT) <= datetime.strptime( end_date, DATE_FMT @@ -96,4 +104,8 @@ def extract(self, region, start_date, end_date, file_path, grid_model, **kwargs) ) if len(missing) > 0: logging.warning(f"There are {len(missing)} files missing") + # Imputing any missing data in place + if not no_impute: + logging.warning("Performing naive gaussian imputing of missing data") + impute.gaussian(data, wind_farms, inplace=True) data.to_pickle(file_path) From e8084ef82d5c29321464ccfee77b757cf02b9ac0 Mon Sep 17 00:00:00 2001 From: Ben RdO Date: Wed, 16 Jun 2021 16:56:41 -0700 Subject: [PATCH 31/61] docs: create index --- docs/index.rst | 95 ++++++++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 95 insertions(+) create mode 100644 docs/index.rst diff --git a/docs/index.rst b/docs/index.rst new file mode 100644 index 000000000..7bfc7a778 --- /dev/null +++ b/docs/index.rst @@ -0,0 +1,95 @@ +PreREISE +========= +This page is dedicated to the collection, processing and formatting of data that are +fed to the simulation engine. PreREISE is an open source package written in Python that +is available on `GitHub `_. + +The generation of input data rely on the grid model. For this reason, you must have +`PowerSimData `_ cloned in a +folder adjacent to your clone of PreREISE. + +.. note:: + Input data are publicly available for the Breakthrough Energy Sciences (BES) grid + model (see `publication `_). You don't need to + generate any input data if you use the scenario framework to carry out power flow + study. + + +General Comments +---------------- +Profiles are CSV (Comma Separated Values) files enclosing a series of data points +indexed in time orders. The simulation engine expects a demand, hydro, solar and wind +profile. All the profiles have UTC timestamp as indices. Columns are the zone IDs and +plant IDs for the demand and hydro/solar/wind profiles, respectively. Values are load in +MWh in each zone for the demand and energy generated by a 1MW generator for hydro, +solar and wind profiles. + +The **[type]_v[D]** naming convention is used, where: + ++ **type** specifies the profile type (demand, hydro, solar or wind) and ++ **D** refers to the date the file has been created using the 3 letters Month (e.g., + Jan) and 4 digits Year (e.g., 2021) format. + +If two or more profiles of the same type are created the same month of the same year, +the different versions will be differentiated using a lowercase letter added right +after the year, e.g, ``demand_vJan2021.csv`` (first), ``demand_vJan2021b.csv`` (second), +``demand_vJan2021c.csv`` (third) and so forth. + + +Demand +------ +Historical +++++++++++ +.. include:: + demand/historical/texas.rst + +.. include:: + demand/historical/western.rst + +.. include:: + demand/historical/eastern.rst + + +NREL Electrification Futures Study Demand and Flexibility Data +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ +.. include:: + demand/nrel/efs.rst + + +Hydro +----- +.. include:: + hydro/texas.rst + +.. include:: + hydro/western.rst + +.. include:: + hydro/eastern.rst + + +Renewables +---------- +Solar ++++++ +.. include:: + renewables/solar/nsrdb.rst + +.. include:: + renewables/solar/method.rst + +Wind +++++ +.. include:: + renewables/wind/rap.rst + +.. include:: + renewables/wind/method.rst + +Resources ++++++++++ +.. include:: + renewables/download.rst + +.. include:: + renewables/notebook.rst From 351cbc1fe5da2bab7f8ebb74f1024fbb9f84022e Mon Sep 17 00:00:00 2001 From: Ben RdO Date: Thu, 8 Jul 2021 14:31:32 -0700 Subject: [PATCH 32/61] docs: write renewables download section --- docs/renewables/download.rst | 70 ++++++++++++++++++++++++++++++++++++ 1 file changed, 70 insertions(+) create mode 100644 docs/renewables/download.rst diff --git a/docs/renewables/download.rst b/docs/renewables/download.rst new file mode 100644 index 000000000..8458b383b --- /dev/null +++ b/docs/renewables/download.rst @@ -0,0 +1,70 @@ +Command Line Interface +++++++++++++++++++++++ +Wind and solar data can be downloaded via our download manager python script. When in +the terminal at the project root directory, you can run: + +.. code:: shell + + python -m prereise.cli.download.download_manager -h + usage: download_manager.py [-h] {wind_data_rap,solar_data_ga,solar_data_nsrdb} ... + + positional arguments: + {wind_data_rap,solar_data_ga,solar_data_nsrdb} + wind_data_rap Download wind data from National Centers for Environmental Prediction + solar_data_ga Download solar data from the Gridded Atmospheric Wind Integration National Dataset Toolkit + solar_data_nsrdb Download solar data from the National Solar Radiation Database + + optional arguments: + -h, --help show this help message and exit + +Currently supported data sources to download from are: + ++ Rapid Refresh from National Centers for Environmental Prediction: + +.. code:: shell + + python -m prereise.cli.download.download_manager wind_data_rap \ + --region REGION \ + --start_date START_DATE \ + --end_date END_DATE \ + --file_path FILEPATH + ++ Gridded Atmospheric Wind Integration National Dataset Toolkit: + +.. code:: + + python -m prereise.cli.download.download_manager solar_data_ga \ + --region REGION \ + --start_date START_DATE \ + --end_date END_DATE \ + --file_path FILEPATH \ + --key API_KEY + ++ The National Solar Radiation Database: + +.. code:: + + python -m prereise.cli.download.download_manager solar_data_nsrdb \ + --region REGION \ + --method METHOD \ + --year YEAR \ + --file_path FILEPATH \ + --email EMAIL \ + --key API_KEY + +As a concrete example, if you would like to download the wind data from Rapid Refresh +from National Centers for Environmental Prediction for the Texas and Western +interconnections between the dates of June 5th, 2020 and January 2nd, 2021 into +``data.pkl``, you can run: + +.. code:: shell + + python -m prereise.cli.download.download_manager wind_data_rap \ + --region Texas \ + --region Western \ + --start_date 2020-05-06 \ + --end_date 2021-01-02 \ + --file_path ./data.pkl + +Note that missing data, if existing, will be imputed using a naive Gaussian algorithm. +This can be avoided using the ``--no_impute`` flag. From 67d25e52d4240e6cf3376e76305c30d2e690679e Mon Sep 17 00:00:00 2001 From: Ben RdO Date: Fri, 9 Jul 2021 13:18:41 -0700 Subject: [PATCH 33/61] docs: write renewables notebook section --- docs/renewables/notebook.rst | 15 +++++++++++++++ 1 file changed, 15 insertions(+) create mode 100644 docs/renewables/notebook.rst diff --git a/docs/renewables/notebook.rst b/docs/renewables/notebook.rst new file mode 100644 index 000000000..0d4d81cf3 --- /dev/null +++ b/docs/renewables/notebook.rst @@ -0,0 +1,15 @@ +Notebooks ++++++++++ +The `RAP notebook`_ fetches the data, imputes missing data and generates a profile. + +The `NSRDB SAM notebook`_ generates a solar profile by feeding the NSRDB data to +SAM while the `NSRDB naive notebook`_ uses the naive method. + +The `GA WIND naive notebook`_ generates solar profiles by applying the naive method to +the Gridded Atmospheric Wind Integration National Dataset. + + +.. _RAP notebook: https://github.com/Breakthrough-Energy/PreREISE/blob/develop/prereise/gather/winddata/rap/demo/rap_demo.ipynb +.. _NSRDB SAM notebook: https://github.com/Breakthrough-Energy/PreREISE/blob/develop/prereise/gather/solardata/nsrdb/demo/nsrdb_sam_demo.ipynb +.. _NSRDB naive notebook: https://github.com/Breakthrough-Energy/PreREISE/blob/develop/prereise/gather/solardata/nsrdb/demo/nsrdb_naive_demo.ipynb +.. _GA WIND naive notebook: https://github.com/Breakthrough-Energy/PreREISE/blob/develop/prereise/gather/solardata/ga_wind/demo/ga_wind_demo.ipynb From 8bd6e28776f22af0141510a322aff8d141becc4f Mon Sep 17 00:00:00 2001 From: Ben RdO Date: Wed, 16 Jun 2021 16:57:39 -0700 Subject: [PATCH 34/61] docs: write wind section --- docs/renewables/wind/method.rst | 27 +++++++++++++++++++++++++++ docs/renewables/wind/rap.rst | 13 +++++++++++++ 2 files changed, 40 insertions(+) create mode 100644 docs/renewables/wind/method.rst create mode 100644 docs/renewables/wind/rap.rst diff --git a/docs/renewables/wind/method.rst b/docs/renewables/wind/method.rst new file mode 100644 index 000000000..1db033794 --- /dev/null +++ b/docs/renewables/wind/method.rst @@ -0,0 +1,27 @@ +From Wind Speed to Power Output +############################### +Once the U and V components of the wind are converted to a non-directional wind speed +magnitude, this speed is converted to power using wind turbine power curves. Since real +wind farms are not currently mapped to a grid network farms, a capacity-weighted average +wind turbine power curve is created for each state based on the turbine types reported +in `EIA Form 860`_. The wind turbine curve for each real wind farm is looked up from a +database of curves (or the *IEC class 2* power curve provided by NREL in the `WIND +documentation`_ is used for turbines without curves in the database), and scaled from +the real hub heights to 80m hub heights using an alpha of 0.15. These height-scaled, +turbine-specific curves are averaged to obtain a state curve translating wind speed to +normalized power. States without wind farms in `EIA Form 860`_ are represented by the +*IEC class 2* power curve. + +Each turbine curve represents the instantaneous power from a single turbine for a given +wind speed. To account for spatio-temporal variations in wind speed (i.e. an hourly +average wind speed that varies through the hour, and a point-specific wind speed that +varies throughout the wind farm), a distribution is used: a normal distribution with +standard deviation of 40% of the average wind speed. This distribution tends to boost +the power produced at lower wind speeds (since the power curve in this region is convex) +and lower the power produced at higher wind speeds (since the power curve in this region +is concave as the turbine tops out, and shuts down at higher wind speeds). This tracks +with the wind-farm level data shown in NREL's validation report. + + +.. _WIND documentation: https://www.nrel.gov/docs/fy14osti/61714.pdf +.. _EIA form 860: https://www.eia.gov/electricity/data/eia860/ diff --git a/docs/renewables/wind/rap.rst b/docs/renewables/wind/rap.rst new file mode 100644 index 000000000..be9b0d1dc --- /dev/null +++ b/docs/renewables/wind/rap.rst @@ -0,0 +1,13 @@ +Rapid Refresh +############# +`RAP`_ (Rapid Refresh) is the continental-scale NOAA hourly-updated +assimilation/modeling system operational at the National Centers for Environmental +Prediction (NCEP). RAP covers North America and is comprised primarily of a numerical +weather model and an analysis system to initialize that model. RAP provides for every +hour ranging from May 2012 to date, the U and V components of the wind speed at 80 meter +above ground on a 13x13 square kilometer resolution grid every hour. Data can be +retrieved using the `NetCDF`_ Subset Service. + + +.. _RAP: https://rapidrefresh.noaa.gov/ +.. _NetCDF: https://www.unidata.ucar.edu/software/thredds/current/tds/reference/NetcdfSubsetServiceReference.html From f9fb3c9a47643d22333e7e7592f3aa132e5bcd5a Mon Sep 17 00:00:00 2001 From: Ben RdO Date: Wed, 16 Jun 2021 16:57:56 -0700 Subject: [PATCH 35/61] docs: write solar section --- docs/renewables/solar/method.rst | 35 ++++++++++++++++++++++++++++++++ docs/renewables/solar/nsrdb.rst | 15 ++++++++++++++ docs/renewables/solar/wind.rst | 9 ++++++++ 3 files changed, 59 insertions(+) create mode 100644 docs/renewables/solar/method.rst create mode 100644 docs/renewables/solar/nsrdb.rst create mode 100644 docs/renewables/solar/wind.rst diff --git a/docs/renewables/solar/method.rst b/docs/renewables/solar/method.rst new file mode 100644 index 000000000..16fe586ed --- /dev/null +++ b/docs/renewables/solar/method.rst @@ -0,0 +1,35 @@ +From Solar Irradiance to Power Output +##################################### +Naive +^^^^^ +Power output is estimated using a simple normalization procedure. For each solar plant +location in the grid model the hourly Global Horizontal Irradiance (GHI) is divided by +the maximum GHI over the period considered. This procedure is referred to as naive since +other factors can possibly affect the conversion from solar radiation at ground to power +such as the temperature at the site as well as many system configuration including +tracking technology. + + +System Adviser Model +^^^^^^^^^^^^^^^^^^^^ +The `System Adviser Model `_ (SAM) developed by NREL is used to +estimate the power output of a solar plant. Irradiance data along with other +meteorological parameters must first be retrieved from NSRDB for each plant site. This +information is then fed to the SAM Simulation Core (SCC) and the power output is +retrieved. The `PySAM`_ Python package provides a wrapper around the SAM library. The +`PVWatts v7 `_ +model is used for all the solar plants in the grid. The system size (in DC units) and +the array type (fixed open rack, backtracked, 1-axis and 2-axis) is set for each solar +plant whereas a unique value of 1.25 is used for the DC to AC ratio (see `article +`_ from EIA on inverter loading +ratios). Otherwise, all other input parameters of the PVWatts model are set to their +default values. `EIA form 860`_ reports the array type used by each solar PV plant. For +each solar plant in our network, the array type is a combination of the three +technology and calculated via the capacity weighted average of the array type of all +the plants in the EIA form that are located in the same state. If no solar plants are +reported in the form for a particular state, we then consider plants belonging to the +same interconnect. + + +.. _PySAM: https://sam.nrel.gov/software-development-kit-sdk/pysam.html +.. _EIA form 860: https://www.eia.gov/electricity/data/eia860/ diff --git a/docs/renewables/solar/nsrdb.rst b/docs/renewables/solar/nsrdb.rst new file mode 100644 index 000000000..1f621637a --- /dev/null +++ b/docs/renewables/solar/nsrdb.rst @@ -0,0 +1,15 @@ +The National Solar Radiation Database +##################################### +The `National Solar Radiation Database `_ (NSRDB) provides +1-hour resolution solar radiation data, ranging from 1998 to 2017, for the entire U.S. +and a growing list of international locations on a 4x4 square kilometer grid. The +`Physical Solar Model`_ (PSM) v3 is the version of the NSRDB used. + +An `API `_ can be used to fetch the +data. A key is required to access and use the above databases. Get your own API key +`here `_. + + +.. _Physical Solar Model: https://nsrdb.nrel.gov/about/u-s-data.html +.. _PySAM: https://sam.nrel.gov/software-development-kit-sdk/pysam.html +.. _EIA form 860: https://www.eia.gov/electricity/data/eia860/ diff --git a/docs/renewables/solar/wind.rst b/docs/renewables/solar/wind.rst new file mode 100644 index 000000000..e925bfe57 --- /dev/null +++ b/docs/renewables/solar/wind.rst @@ -0,0 +1,9 @@ +Gridded Atmospheric Wind Integration National Dataset +##################################################### +The `Gridded Atmospheric WIND (Wind Integration National Dataset) Toolkit +`_ provides 1-hour resolution irradiance +data for 7 years, ranging from 2007 to 2013, on a uniform 2x2 square kilometer grid +that covers the continental U.S., the Baja Peninsula, and parts of the Pacific and +Atlantic oceans. Data can be accessed using the Highly Scalable Data Service. NREL +wrote `example notebooks `_ that demonstrate how +to access the data. From 1f3d310d6d522219e7f66764a172bc7463bd13af Mon Sep 17 00:00:00 2001 From: Ben RdO Date: Wed, 23 Jun 2021 15:33:37 -0700 Subject: [PATCH 36/61] docs: write hydro section --- docs/hydro/eastern.rst | 35 +++++++++++++++++++++++++++ docs/hydro/legacy/capacity_factor.rst | 13 ++++++++++ docs/hydro/texas.rst | 13 ++++++++++ docs/hydro/western.rst | 30 +++++++++++++++++++++++ 4 files changed, 91 insertions(+) create mode 100644 docs/hydro/eastern.rst create mode 100644 docs/hydro/legacy/capacity_factor.rst create mode 100644 docs/hydro/texas.rst create mode 100644 docs/hydro/western.rst diff --git a/docs/hydro/eastern.rst b/docs/hydro/eastern.rst new file mode 100644 index 000000000..0cf219c33 --- /dev/null +++ b/docs/hydro/eastern.rst @@ -0,0 +1,35 @@ +Eastern ++++++++ +Profile generation for the Eastern Interconnection is slightly more complex than for +the Western Interconnection. First, we handle pumped storage hydro (HPS) and +conventional hydro (HYC) separately. Then, in addition to using the net demand profile +to derive the profile of conventional hydro plants in some state as we did for +California, we also use historical hourly total hydro generation time series in some +regions. + + ++ **Pumped Storage Hydro**: We identified hydro plants in our grid model that + are closely located to known HPS site in the Eastern Interconnection and created a + template to describe the hourly energy generation. The plant level profile is + generated considering the local time and daylight-saving schedule of the + corresponding bus location. ++ **Conventional hydro**: profiles provided by `ISONE`_, `NYISO`_, `PJM`_ and `SPP`_ + are used for plants located within the area they cover. For states that are not at + all covered or partially covered by the 4 ISOs the net demand demand is used as a + template to derive the hydro profile using the same method that has been developed + for California, i.e., the monthly net demand is normalized such that its + sum is equal to the historical monthly total hydro generation (reported in `EIA form + 923`_) divided by the available total hydro capacity in the grid model. Note that for + partially covered states, the historical monthly total hydro generation in the state + is split proportionally to the available total hydro capacity in the grid model for + the state and only the portion outside the ISOs is used during the normalization. + + +The `eastern hydro notebook`_ generates the profile. + + +.. _ISONE: https://www.iso-ne.com/isoexpress/ +.. _NYISO: http://mis.nyiso.com/public/P-63list.htm +.. _PJM: http://dataminer2.pjm.com/feed/gen_by_fuel +.. _SPP: https://marketplace.spp.org/pages/generation-mix-historical +.. _eastern hydro notebook: https://github.com/Breakthrough-Energy/PreREISE/blob/develop/prereise/gather/hydrodata/eia/demo/eastern_hydro_v3_demo/eastern_hydro_v3_demo.ipynb diff --git a/docs/hydro/legacy/capacity_factor.rst b/docs/hydro/legacy/capacity_factor.rst new file mode 100644 index 000000000..f8bb8d733 --- /dev/null +++ b/docs/hydro/legacy/capacity_factor.rst @@ -0,0 +1,13 @@ +Capacity Factor ++++++++++++++++ +EIA publishes US average monthly capacity factors for hydro plants. The `table +`_` is used to +produce a profile for each hydro plant in the grid. + +Note that we are using the same set +of capacity factors independently of the geographical location of the plant and, as a +result, the profile of all the hydro plants in the grid will have the same shape. + +Check out the `hydro capacity factor notebook`_ for a demo. + +.. _hydro capacity factor notebook: https://github.com/Breakthrough-Energy/PreREISE/blob/develop/prereise/gather/hydrodata/eia/demo/hydro_v1_demo.ipynb diff --git a/docs/hydro/texas.rst b/docs/hydro/texas.rst new file mode 100644 index 000000000..87127e18c --- /dev/null +++ b/docs/hydro/texas.rst @@ -0,0 +1,13 @@ +Texas ++++++ +ERCOT publishes actual generation by fuel type for each 15 minute settlement interval +(see the `fuel mix report`_ for more details). The profile of each hydro plant in the +Texas Interconnection is then simply the ratio of the total generation provided by ERCOT +divided by the total hydro capacity available in the Texas Interconnection of the grid +model. + +The `texas hydro notebook`_ generates the profile. + + +.. _fuel mix report: http://www.ercot.com/gridinfo/generation/ +.. _texas hydro notebook: https://github.com/Breakthrough-Energy/PreREISE/blob/develop/prereise/gather/hydrodata/eia/demo/texas_hydro_v2_demo.ipynb diff --git a/docs/hydro/western.rst b/docs/hydro/western.rst new file mode 100644 index 000000000..0fe972651 --- /dev/null +++ b/docs/hydro/western.rst @@ -0,0 +1,30 @@ +Western ++++++++ +Unlike Texas, we don't have access to hourly (or sub-hourly) total generation by state +or even for the whole Western Interconnection. We rely on three different methods to +derive the shape of the hydro profile in California, Wyoming and the rest of the Western Interconnection. + ++ **California**: we use the net demand profile as a template. This is supported by data + from California ISO (see `CAISO outlook`_) showing that the hydro generation profile + closely follows the net demand profile. ++ **Wyoming**: we simply apply a constant shape curve to avoid peak-hour violation of + maximum capacity since hydro generators have a small name plate capacities. ++ **other region in the Western Interconnection**: we use the aggregated generation of + the top 20 US Army Corps managed hydro dams in Northwestern US (primarily located in + the state of Washington) as the shape of the hydro profile since WA has the most hydro + generation in the Western Interconnection. The data is obtained via the US Army Corps + of Engineers Northwestern Division DataQuery Tool 2.0 (see `USACE dataquery`_). + + +The above curves are then normalized such that the monthly sum in each of the above +regions is equal to the total monthly hydro generation divided by the total hydro +capacity available in the grid model for the region. Note that `EIA form 923` provides +the historical monthly total hydro generation by state. + +The `western hydro notebook`_ generates the profile. + + +.. _CAISO outlook: http://www.caiso.com/TodaysOutlook/Pages/default.aspx +.. _USACE dataquery: https://www.nwd-wc.usace.army.mil/dd/common/dataquery/www/ +.. _EIA form 923: https://www.eia.gov/electricity/data/eia923/ +.. _western hydro notebook: https://github.com/Breakthrough-Energy/PreREISE/blob/develop/prereise/gather/hydrodata/eia/demo/western_hydro_v2_demo.ipynb From 182c078d9cb287475b616a582a308af23d284dc9 Mon Sep 17 00:00:00 2001 From: Ben RdO Date: Fri, 25 Jun 2021 12:11:43 -0700 Subject: [PATCH 37/61] docs: write nrel efs section --- docs/demand/nrel/efs.rst | 42 ++++++++++++++++++++++++++++++++++++++++ 1 file changed, 42 insertions(+) create mode 100644 docs/demand/nrel/efs.rst diff --git a/docs/demand/nrel/efs.rst b/docs/demand/nrel/efs.rst new file mode 100644 index 000000000..ed42bbad1 --- /dev/null +++ b/docs/demand/nrel/efs.rst @@ -0,0 +1,42 @@ +The National Renewable Energy Laboratory (NREL) has developed the Electrification +Futures Study (EFS) to project and study future sectoral demand changes as a result of +impending widespread electrification. As a part of the EFS, NREL has published multiple +reports (dating back to 2017) that describe their process for projecting demand-side +growth and provide analysis of their preliminary results; all of NREL's published EFS +reports can be found `here +`_. Accompanying their +reports, NREL has published data sets that include hourly load profiles that were +developed using processes described in the EFS reports. These hourly load profiles +represent state-by-state end-use electricity demand across four sectors +(Transportation, Residential Buildings, Commercial Buildings, and Industry) for three +electrification scenarios (Reference, Medium, and High) and three levels of technology +advancements (Slow, Moderate, and Rapid). Load profiles are provided for six separate +years: 2018, 2020, 2024, 2030, 2040, and 2050. The base demand data sets and further +accompanying information can be found `here `_. +In addition to demand growth projections, NREL has also published data sets that +include hourly profiles for flexible load. These data sets indicate the amount of +demand that is considered to be flexible, as determined through the EFS. The +flexibility demand profiles consider two scenarios of flexibility (Base and Enhanced), +in addition to the classifications for each sector, electrification scenario, +technology advancement, and year. The flexible demand data sets and further +accompanying information can be found `here `_. + +Widespread electrification can have a large impact on future power system planning +decisions and operation. While increased electricity demand can have obvious +implications for generation and transmission capacity planning, new electrified demand +(e.g., electric vehicles, air source heat pumps, and heat pump water heaters) offers +large amounts of potential operational flexibility to grid operators. This flexibility +by demand-side resources can result in demand shifting from times of peak demand to +times of peak renewable generation, presenting the opportunity to defer generation and +transmission capacity upgrades. To help electrification impacts be considered properly, +this package has the ability to access NREL's EFS demand data sets. Currently, users can +access the base demand profiles, allowing the impacts of demand growth due to vast +electrification to be explored. Users can also access the EFS flexible demand profiles. + +The `NREL EFS demand notebook`_ and `NREL EFS flexibility notebook`_, illustrate the +functionality of the various modules developed for obtaining and cleaning the NREL's +EFS demand data. + + +.. _NREL EFS demand notebook: https://github.com/Breakthrough-Energy/PreREISE/blob/develop/prereise/gather/demanddata/nrel_efs/demo/efs_demand_reference_slow_2030_demo.ipynb +.. _NREL EFS flexibility notebook: https://github.com/Breakthrough-Energy/PreREISE/blob/develop/prereise/gather/demanddata/nrel_efs/demo/efs_base_flexibility_reference_slow_2030_demo.ipynb From 94077c28e7f7d3c6f8bc335b0557ec24d936954e Mon Sep 17 00:00:00 2001 From: Ben RdO Date: Tue, 29 Jun 2021 09:28:27 -0700 Subject: [PATCH 38/61] docs: write historical demand section --- docs/demand/historical/eastern.rst | 26 ++++++++++++++++++++++++++ docs/demand/historical/texas.rst | 5 +++++ docs/demand/historical/western.rst | 19 +++++++++++++++++++ 3 files changed, 50 insertions(+) create mode 100644 docs/demand/historical/eastern.rst create mode 100644 docs/demand/historical/texas.rst create mode 100644 docs/demand/historical/western.rst diff --git a/docs/demand/historical/eastern.rst b/docs/demand/historical/eastern.rst new file mode 100644 index 000000000..616f05885 --- /dev/null +++ b/docs/demand/historical/eastern.rst @@ -0,0 +1,26 @@ +Eastern +####### +The construction of the Eastern Interconnection demand profile is slightly different +from the Western counterpart. We still download historical demand data from EIA +and perform the 3-step data processing/cleaning as for the Western Interconnection +for all Balancing Authorities (BAs) but MISO (Midcontinent Independent System Operator) +and SPP (Southwest Power Pool). + +MISO and SPP operate across multiple U.S. states (e.g. 15 for MISO) and cover several +load zones in our grid model. Instead of considering a single hourly profile shape for +each entity and having load zones sharing the exact same profile in different part of +the country, we further split MISO and SPP into subareas. The hourly subarea demand +profiles for MISO and SPP can be downloaded on their respective website (check `SPP +hourly load`_ and `MISO hourly load`_). The geographical definitions of these subareas +are obtained directly from contact at the BAs via either customer service or internal +request management system (see the `RMS`_ for SPP). Given the geographical definitions, +i.e., list of counties for each subarea, each bus within MISO and SPP is mapped to the +subarea it belongs to. + +The overall procedure is is demonstrated in the `eastern demand notebook`_. + + +.. _SPP hourly load: https://marketplace.spp.org/pages/hourly-load +.. _MISO hourly load: https://www.misoenergy.org/markets-and-operations/real-time--market-data/market-reports#nt=%2FMarketReportType%3ASummary%2FMarketReportName%3AHistorical%20Daily%20Forecast%20and%20Actual%20Load%20by%20Local%20Resource%20Zone%20(xls)&t=10&p=0&s=MarketReportPublished&sd=desc +.. _RMS: https://spprms.issuetrak.com/Login.asp +.. _eastern demand notebook: https://github.com/Breakthrough-Energy/PreREISE/blob/develop/prereise/gather/demanddata/eia/demo/eastern_demand_v6_demo/eastern_demand_v6_demo.ipynb diff --git a/docs/demand/historical/texas.rst b/docs/demand/historical/texas.rst new file mode 100644 index 000000000..7c1813f00 --- /dev/null +++ b/docs/demand/historical/texas.rst @@ -0,0 +1,5 @@ +Texas +##### +ERCOT publishes historical hourly load data for its eight weather zones. The data +downloaded `here `_ are used as is to +build the profile for the Texas Interconnection. diff --git a/docs/demand/historical/western.rst b/docs/demand/historical/western.rst new file mode 100644 index 000000000..f0f997869 --- /dev/null +++ b/docs/demand/historical/western.rst @@ -0,0 +1,19 @@ +Western +####### +Balancing authorities (BAs) submit their demand data to EIA and can be downloaded +using an `API `_. The list of BAs in the Western +Interconnection can be found on the website of the Western Electricity Coordinating +Council (WECC) along with the area they approximately cover (see `map`_). + +Some data processing/cleaning is then carried out to derive the profile for the Western +Interconnection: + ++ adjacent data are used to fill out missing values ++ BAs are aggregated into the load zones of the grid model ++ outliers are detected and fixed. + +These steps are illustrated in the `western demand notebook`_. + + +.. _map: https://www.wecc.org/Administrative/Balancing_Authorities_JAN17.pdf +.. _western demand notebook: https://github.com/Breakthrough-Energy/PreREISE/blob/develop/prereise/gather/demanddata/eia/demo/western_demand_v4_demo/western_demand_v4_demo.ipynb From f3777f61379e850585030634afce60f97df2fbae Mon Sep 17 00:00:00 2001 From: Ben RdO Date: Tue, 27 Jul 2021 15:13:04 -0700 Subject: [PATCH 39/61] docs: rewrite README (#195) --- README.md | 773 ++++-------------------------------------------------- 1 file changed, 46 insertions(+), 727 deletions(-) diff --git a/README.md b/README.md index cebc95fe8..8b9a41b90 100644 --- a/README.md +++ b/README.md @@ -1,757 +1,76 @@ ![logo](https://raw.githubusercontent.com/Breakthrough-Energy/docs/master/source/_static/img/BE_Sciences_RGB_Horizontal_Color.svg) -[![codecov](https://codecov.io/gh/Breakthrough-Energy/PreREISE/branch/develop/graph/badge.svg?token=4KA0ESPUA4)](https://codecov.io/gh/Breakthrough-Energy/PreREISE) +[![codecov](https://codecov.io/gh/Breakthrough-Energy/PreREISE/branch/develop/graph/badge.svg?token=UFZ9CW4GND)](https://codecov.io/gh/Breakthrough-Energy/PreREISE) [![made-with-python](https://img.shields.io/badge/Made%20with-Python-1f425f.svg)](https://www.python.org/) [![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black) ![Tests](https://github.com/Breakthrough-Energy/PreREISE/workflows/Pytest/badge.svg) [![Documentation](https://github.com/Breakthrough-Energy/docs/actions/workflows/publish.yml/badge.svg)](https://breakthrough-energy.github.io/docs/) +![GitHub contributors](https://img.shields.io/github/contributors/Breakthrough-Energy/PreREISE?logo=GitHub) +![GitHub commit activity](https://img.shields.io/github/commit-activity/m/Breakthrough-Energy/PreREISE?logo=GitHub) +![GitHub last commit (branch)](https://img.shields.io/github/last-commit/Breakthrough-Energy/PreREISE/develop?logo=GitHub) +![GitHub pull requests](https://img.shields.io/github/issues-pr/Breakthrough-Energy/PreREISE?logo=GitHub) [![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT) +[![Code of Conduct](https://img.shields.io/badge/code%20of-conduct-ff69b4.svg?style=flat)](https://breakthrough-energy.github.io/docs/communication/code_of_conduct.html) -# PreREISE -This package gathers and builds demand, hydro, solar, and wind profiles. The profiles -are needed to run scenarios on the U.S. electrical grid. PreREISE is part of a set of -packages representing Breakthrough Energy's power system model. - -More information regarding the installation of the model as well as the contribution -guide can be found [here](https://breakthrough-energy.github.io/docs/). - - -## 1. Setup/Install -Here are the instructions to install the **PreREISE** package. We strongly recommend -that you pick one of the following options. - -**NOTE: you MUST have -[PowerSimData](https://github.com/Breakthrough-Energy/PowerSimData/) cloned in -a folder adjacent to your clone of PreREISE as the installation of packages -in requirements.txt depends on files in PowerSimData.** - -### A. Using pipenv -If not already done, install `pipenv` by following the instructions on their -[webpage](https://pipenv.pypa.io/en/latest/). If running `pipenv` -does not work after installation, make sure you also followed steps -[here](https://pipenv.pypa.io/en/latest/install/#pragmatic-installation-of-pipenv) -that address modifying your PATH. Then run: -```bash -pipenv sync -pipenv shell -``` -in the root folder of the package. The first command will create a virtual environment -and install the dependencies. The second command will activate the environment. - -### B. Using the ***requirements.txt*** file -First create an environment using `venv` (more details -[here](https://docs.python.org/3/library/venv.html)). Note that `venv` is included in -the Python standard library and requires no additional installation. Then, activate your -environment and run: -```bash -pip install -r requirements.txt -``` -in the root folder of the package. - - -### C. Path -Whatever method you choose, if you wish to access the modules located in **PreREISE** -from anywhere on your machine, do: -```bash -pip install . -``` -in the root folder of your package or alternatively, setup the `PYTHONPATH` global -variable. - - -## 2. Gather Data for Simulation -This module aims at gathering the required data for building the profiles - -### Profile Naming Convention -We call the time series profiles directly generated from mathematical/heuristic models -without any scaling (as we do in different scenarios) as 'raw' profiles. - -The name of a raw profile in the simulation framework must be of the form: - -[**type**]\_v\[**D**], - -where **type** specifies the profile type ('*demand*', '*hydro*', '*solar*', '*wind*') -and **D** refers to the date the file has been created. Month (3 letters, e.g., Jan) and -year (4 digits, e.g., 2021) are used for the date. If two or more profiles of the same -**type** are created the same month of the same year, the different versions will be -differentiated using a lowercase letter added right after the year, e.g, -***demand_vJan2021.csv*** (first), ***demand_vJan2021b.csv*** (second), -***demand_vJan2021c.csv*** (third) and so forth. - - -### How to download - -Most data can be downloaded via our download manager python script. After setting -up the project via the [setup instructions](#1-setupinstall), when in the terminal -at the project root directory, you can run: - -```bash -> python -m prereise.cli.download.download_manager -h -usage: download_manager.py [-h] - {wind_data_rap,solar_data_ga,solar_data_nsrdb} ... - -positional arguments: - {wind_data_rap,solar_data_ga,solar_data_nsrdb} - wind_data_rap Download wind data from National Centers for - Environmental Prediction - solar_data_ga Download solar data from the Gridded Atmospheric Wind - Integration National Dataset Toolkit - solar_data_nsrdb Download solar data from the National Solar Radiation - Database - -optional arguments: - -h, --help show this help message and exit -``` -Currently supported data sources to download from are: - -[Rapid Refresh from National Centers for Environmental Prediction](#i-rapid-refresh) - -```bash -python -m prereise.cli.download.download_manager wind_data_rap \ - --region REGION \ - --start_date START_DATE \ - --end_date END_DATE \ - --file_path FILEPATH -``` - -[Gridded Atmospheric Wind Integration National Dataset Toolkit](#i-the-gridded-atmospheric-wind-integration-national-dataset-toolkit) -```bash -python -m prereise.cli.download.download_manager solar_data_ga \ - --region REGION \ - --start_date START_DATE \ - --end_date END_DATE \ - --file_path FILEPATH \ - --key API_KEY -``` - -[The National Solar Radiation Database](#ii-the-national-solar-radiation-database) -```bash -python -m prereise.cli.download.download_manager solar_data_nsrdb \ - --region REGION \ - --method METHOD \ - --year YEAR \ - --file_path FILEPATH \ - --email EMAIL \ - --key API_KEY -``` - -As a concrete example, if you would like to download the wind data from Rapid -Refresh from National Centers for Environmental Prediction for regions Texas and Western -between the dates of June 5th, 2020 and Janurary 2nd, 2021 into data.pkl, you can run: -```bash -python -m prereise.cli.download.download_manager wind_data_rap \ - --region Texas \ - --region Western \ - --start_date 2020-05-06 \ - --end_date 2021-01-02 \ - --file_path ./data.pkl -``` -You can run `python -m prereise.cli.download.download_manager DATA_SOURCE_OPTION -h` for more -details, where `DATA_SOURCE_OPTION` is `wind_data_rap`, `solar_data_nsrdb`, etc. - -### A. Wind data - -#### i. Rapid Refresh -[RAP][RAP] (Rapid Refresh) is the continental-scale NOAA hourly-updated -assimilation/modeling system operational at the National Centers for Environmental -Prediction (NCEP). RAP covers North America and is comprised primarily of a numerical -weather model and an analysis system to initialize that model. RAP provides, every hour -ranging from May 2012 to date, the U and V components of the wind speed at 80 meter -above ground on a 13x13 square kilometer resolution grid every hour. Data can be -retrieved using the NetCDF Subset Service. Information on this interface is described -[here][NetCDF]. Note that the dataset is incomplete and, consequently, missing entries -need to be imputed. - -Once the U and V components of the wind are converted to a non-directional wind speed -magnitude, this speed is converted to power using wind turbine power curves. Since real -wind farms are not currently mapped to TAMU network farms, a capacity-weighted average -wind turbine power curve is created for each state based on the turbine types reported -in [EIA Form 860][EIA 860]. The wind turbine curve for each real wind farm is looked up -from a database of curves (or the *IEC class 2* power curve provided by NREL in the -[WIND Toolkit documentation][WIND_doc]) is used for turbines without curves in the -database), and scaled from the real hub heights to 80m hub heights using an alpha of -0.15. These height-scaled, turbine-specific curves are averaged to obtain a state curve -translating wind speed to normalized power. States without wind farms in -[EIA Form 860][EIA 860] are represented by the *IEC class 2* power curve. - -Each turbine curve represents the instantaneous power from a single turbine for a given -wind speed. To account for spatio-temporal variations in wind speed (i.e. an hourly -average wind speed that varies through the hour, and a point-specific wind speed that -varies throughout the wind farm), a distribution is used: a normal distribution with -standard deviation of 40% of the average wind speed. This distribution tends to boost -the power produced at lower wind speeds (since the power curve in this region is convex) -and lower the power produced at higher wind speeds (since the power curve in this region -is concave as the turbine tops out, and shuts down at higher wind speeds). This tracks -with the wind-farm level data shown in NREL's validation report. - -Check out the **[rap_demo.ipynb][RAP_notebook]** notebook for demo. - - -### B. Solar data - -#### i. The Gridded Atmospheric Wind Integration National Dataset Toolkit -The [Gridded Atmospheric WIND (Wind Integration National Dataset) Toolkit][WIND_web] -provides 1-hour resolution irradiance data for 7 years, ranging from 2007 to 2013, on a -uniform 2x2 square kilometer grid that covers the continental U.S., the Baja Peninsula, -and parts of the Pacific and Atlantic oceans. Data can be accessed using the Highly -Scalable Data Service. NREL wrote [example notebooks][NREL_notebooks] that demonstrate -how to access the data. - -Power output is estimated using a simple normalization procedure. For each solar plant -location the hourly Global Horizontal Irradiance (GHI) is divided by the maximum GHI -over the period considered and multiplied by the capacity of the plant. This procedure -is referred to as naive since it only accounts for the plant capacity. Note that other -factors can possibly affect the conversion from solar radiation at ground to power such -as the temperature at the site as well as many system configuration including tracking -technology. - -Check out the **[ga_wind_demo.ipynb][GA_WIND_notebook]** notebook for demo. - -#### ii. The National Solar Radiation Database -[NSRDB (National Solar Radiation Database)][NSRDB_web] provides 1-hour resolution solar -radiation data, ranging from 1998 to 2016, for the entire U.S. and a growing list of -international locations on a 4x4 square kilometer grid. Data can be accessed via an -[API][NSRDB_api]. Note that the Physical Solar Model v3 is used. - -An API key is required to access and use the above databases. Get your own API key -[here][NSRDB_signup]. - -Here, the power output can be estimated using the previously presented naive method or a -more sophisticated one. The latter uses the System Adviser Model ([SAM][SAM_web]) -developed by NREL. The developer tools for creating renewable energy system models can -be downloaded [here][SAM_sdk]. Irradiance data along with other meteorological -parameters must first be retrieved from NSRDB for each site. This information are then -fed to the SAM Simulation Core (SCC) and the power output is retrieved. The SSC reflect -the technology used: photovoltaic (PV), solar water heating and concentrating solar -power (CSP). The [*PVWatts v7*][SAM_pvwatts] model is used for all the solar plants in -the grid. The system size (in DC units) and the array type (fixed open rack, -backtracked, 1-axis and 2-axis) is set for each solar plant whereas a unique value of -1.25 is used for the DC to AC ratio (see article from EIA on inverter loading ratios -[here](https://www.eia.gov/todayinenergy/detail.php?id=35372)). Otherwise, all other -input parameters of the *PVWatts* model are set to their default values. EIA reports in -[form 860][EIA 860] the array type used by each solar PV plant. For each plant in our -network, the array type is a combination of the three technology that is calculated -using the capacity weighted average of the array type of all the plants in -[EIA Form 860][EIA 860] that are located in the same state. If no plants are reported -in [EIA Form 860][EIA 860] for a particular state we then use the information of all -the plants belonging to the same interconnect. - -The naive and the SAM methods are used in the -**[nsrdb_naive_demo.ipynb][NSRDB_naive_notebook]** and -**[nsrdb_sam_demo.ipynb][NSRDB_sam_notebook]** demo notebooks, respectively. - - -### C. Hydro Data - -#### i. Hydro v1 -EIA (Energy Information Administration) published monthly capacity factors for hydro -plants across the country. This dataset (available [here][hydro_cf]) is used to produce -a profile for each hydro plant in the grid. Note that we are using the same set of -capacity factor independently of the geographical location of the plant. As a result, -the profile of all the hydro plants in the grid will have the same shape. Only the power -output will differ (the scale of the profile). - -Check out the **[hydro_v1_demo.ipynb][hydro_v1_notebook]** notebook for demo. -#### ii. Hydro v2 -##### a. Western -Hydro hourly profile v2 for Western consists of two components: profile shape to capture -the hourly variance and monthly total generation to capture the historical summation. -EIA published monthly total generation for each hydro plant by state in form EIA 923 -(available [here][EIA 923]). - -Given that Washington state has the most hydro generation in the Western -Interconnection, we use the aggregated generation of the top 20 US Army Corps managed -hydro dams in Northwestern US (primarily in WA) as the shape of this hydro profile v2 -for all the states in Western except for California and Wyoming. The data is obtained -via [US Army Corps of Engineers Northwestern Division DataQuery Tool -2.0][USACE_dataquery]. - -Observed from system daily outlook of California ISO (available [here][CAISO_outlook]), -the hydro generation profile follows closely to the net demand profile. Thus, we -construct the shape curve of hydro profile v2 in CA using the net demand profile of CA -in the base case scenario (Scenario 87). As for Wyoming, due to the small name plate -capacities of the hydro generators, we simply apply a constant shape curve to avoid -peak-hour violation of maximum capacity. - -The final hydro profile v2 is built by scaling the corresponding shape curves based on -the monthly total generation record in each state, then decomposing into plant-level -profiles proportional to the generator capacities. Check out the -**[western_hydro_v2_demo.ipynb][hydro_v2_western_notebook]** notebook for demo. - -##### b.Texas -The Electric Reliability Council of Texas (ERCOT) published actual generation by fuel -type for each 15 minute settlement interval. For details, see the fuel mix report -available [here][ERCOT_generation]. Given this time-series historical data, similarly -with the western case, the final hydro profile v2 for Texas is constructed by -decomposing the total hydro generation profile proportional to the generator capacities. -Check out the **[texas_hydro_v2_demo.ipynb][hydro_v2_texas_notebook]** notebook for -demo. - -#### iii. Hydro v3 -This methodology is designed to generate hourly plant level hydro profile for Eastern, -i.e. eastern hydro v3, which has following features: - -- Pumped storage hydro (HPS) and conventional hydro (HYC) are handled separately. -- Historical hourly hydro profiles of four ISOs (ISONE, NYISO, PJM and SPP), are used -directly as regional total hydro profiles to start with. -- For the rest of areas in Eastern Interconnect, which are not covered by the four -ISOs, the hydro profile is generated in the same way as western hydro profile v2. - -Note that usa hydro v3 is the concatenation of eastern hydro v3, western hydro v2 and -texas hydro v2 - -##### a. Pumped Storage Hydro -HPS profile for each plant in [hps_plants_eastern.xlsx][pumped storage hydro model], -**‘all_plantIDs’** sheet, is generated based on the deterministic model presented in -**‘profile’** sheet. The HPS profile model is designed based on local time. The plant -level HPS profiles are generated considering the local time and daylight-saving schedule -of the locations of the corresponding buses. However, during the sanity check -afterwards, it turns out that this model overestimates the HPS output, the final profile -is further scaled by 0.65 to be in agreement with values reported in [EIA 923][EIA 923]. - -##### b. Conventional Hydro -The buses of the HYC plants were associated to five regions (ISONE, NYISO, PJM, SPP and -the area uncovered by the aforementioned regions) using the same methodology employed -for eastern demand v5. Check Demand Data section below for details. For HYC plants -locating inside the territories of the four ISOs, we decompose the total historical -profile of each ISO into plant -level profiles proportional to the generator capacities. -The time series profile data of each ISO is obtained via their official websites: -[ISONE][ISO New England], [NYISO][NY ISO], [PJM][PJM], [SPP][Southwest Power Pool]. - -For the rest of HYC plants lying outside the four ISO regions, we apply the same -methodology that is used to generate hydro profile of California in Western hydro v2 -(see details in the above subsection). The net demand profile is obtained from Eastern -base case scenario (Scenario 397). The monthly net generations for a state is split -proportional to the total capacities of the generators if the corresponding state is -covered partially by the four ISOs mentioned above. - -The final Eastern hydro profile v3 is built by stitching the three parts together: -pumped storage hydro profiles, conventional hydro profiles within the four ISO regions -and conventional hydro profiles in the rest areas . Check out -**[eastern_hydro_v3_demo.ipynb][hydro_v3_eastern_notebook ]** notebook for demo. - -### D. Demand Data - -*Eastern V6* - -The two BAs, SPP and MISO, consist of big areas from north to south. It is unlikely that -the whole area covered by these big BAs have the same hourly profile shape. Eastern -demand v6 addresses the issue by further splitting these two BAs into subareas. We -replace overall MISO and SPP demand with subarea demand obtained directly from contact -at the BAs. We use overall numbers from EIA and use the fractional subarea demand as the -basis to split the MISO and SPP demand. - -The hourly subarea demand profiles for SPP and MISO is reported on their official -websites respectively (check [SPP hourly -load](https://marketplace.spp.org/pages/hourly-load), [MISO hourly -load](https://www.misoenergy.org/markets-and-operations/real-time--market-data/market-reports/#nt=%2FMarketReportType%3ADay-Ahead&t=10&p=0&s=MarketReportPublished&sd=desc)). -The geographical definitions of these subareas are obtained directly from contact at the -BAs via either customer service or internal request management system (check -[RMS](https://spprms.issuetrak.com/Login.asp)). Given the geographical definitions, i.e. -list of counties for each subarea, each bus is mapped to the subarea it belongs to. - -The overall procedure is similar to v5 except we generate subarea mapping as well as prepare subarea demand from files. - -*Eastern V5* - -Demand data are obtained from EIA, to whom Balancing Authorities have submitted their -data. The data can be obtained using an API as demonstrated in -**[eastern_demand_v5_demo.ipynb][eastern_demand_v5_demo]** notebook. - -Module `get_eia_data` contains functions that converts the data into data frames for -further processing, as performed in -**[eastern_demand_v5_demo.ipynb][eastern_demand_v5_demo]**. - -To output the demand profile, cleaning steps were applied to the EIA data for Eastern -V5. We used adjacent demand data to fill missing values using a series of rules: - -1. Monday: look forward one day -2. Tuesday - Thursday: average of look forward one day and look back one day -3. Friday: look back one day -4. Saturday: look forward one day -5. Sunday: look back one day - -If data is still missing after applying the above rules, week ahead and week behind data -is used: - -1. Monday: look forward two days -2. Tuesday: look forward two days -3. Wednesday: average of look forward two days and look back two days -4. Thursday: look back two days -5. Friday: look back two days -6. Saturday - Sun: average of look back one week and look forward one week - -If data is still missing after applying the above rules, week ahead and week behind data -is used: - -1. Monday - Sunday: average of look back one week and look forward one week - -The next step was outlier detection. The underlying physical rationale is that demand -changes are mostly driven by weather temperature changes (first or higher order), and -thermal mass limits the rate at which demand values can change. Outliers were detected -using a z-score threshold value of 3. These outliers are then replaced by linear -interpolation. - -The BA counts were then distributed across each region where the BA operates, using the -region populations as weights. For example, if a BA operates in both WA and OR, the -counts for WA are weighted by the fraction of the total counts in WA relative to the -total population of WA and OR. - -Lastly, buses were mapped to counties. This step requires an input data file that stores -the list of counties in each BA area territory. Some data cleaning was necessary to deal -with inconsistent county names. We also implemented a check if there are buses where BA -is empty/not found, which is due to bus being outside of United States. These were fixed -manually by assigning the bus to the nearest county. - -*Legacy Description* - -Demand data are obtained from EIA, to whom Balancing Authorities have submitted their -data. The data can be obtained either by direct download from their database using an -API or by download of Excel spreadsheets. An API key is required for the API download -and this key can be obtained by a user by registering at -. - -The direct download currently contains only published demand data. The Excel -spreadsheets include original and imputed demand data, as well as results of various -data quality checks done by EIA. Documentation about the dataset can be found -[here][demand_doc]. Excel spreadsheets can be downloaded by clicking on the links in -page 9 (Table of all US and foreign connected balancing authorities). - -Module `get_eia_data` contains functions that converts the data into data frames for -further processing. - -To test EIA download (This requires an EIA API key): -```python -from prereise.gather.demanddata.eia.tests import test_get_eia_data - -test_get_eia_data.test_eia_download() -``` -To test EIA download from Excel: -```python -from prereise.gather.demanddata.eia.tests import test_get_eia_data - -test_get_eia_data.test_from_excel() -``` - -The **[assemble_ba_from_excel_demo.ipynb][demand_notebook]** notebook illustrates usage. - -To output the demand profile, cleaning steps were applied to the EIA data: 1) missing -data imputation - the EIA method was used, i.e., EIA published data was used; beyond -this, NA's were converted to float zeros; 2) missing hours were added. - -The BA counts were then distributed across each region where the BA operates, using the -region populations as weights. For example, if a BA operates in both WA and OR, the -counts for WA are weighted by the fraction of the total counts in WA relative to the -total population of WA and OR. - -The next step consist in detecting outliers by looking for large changes in the slope of -the demand data. The underlying physical rationale is that demand changes are mostly -driven by weather temperature changes (first or higher order), and thermal mass limits -the rate at which demand values can change. By looking at the slope of demand data, it -is seen that the slope distribution is normally distributed, and outliers can be easily -found by imposing a z-score threshold value of 3. These outliers are then replaced by -linear interpolation. - -To test outlier detection, use: -```python -from prereise.gather.demanddata.eia.tests import test_clean_data - -test_clean_data.test_slope_interpolate() -``` -The **[ba_anomaly_detection_demo.ipynb][demand_anomaly]** notebook illustrates usage. - -### E. NREL Electrification Futures Study Demand and Flexibility Data -The National Renewable Energy Laboratory (NREL) has developed the Electrification -Futures Study (EFS) to project and study future sectoral demand changes as a result of -impending widespread electrification. As a part of the EFS, NREL has published multiple -reports (dating back to 2017) that describe their process for projecting demand-side -growth and provide analysis of their preliminary results; all of NREL's published EFS -reports can be found [here][nrel_efs]. Accompanying their reports, NREL has published -data sets that include hourly load profiles that were developed using processes -described in the EFS reports. These hourly load profiles represent state-by-state -end-use electricity demand across four sectors (Transportation, Residential Buildings, -Commercial Buildings, and Industry) for three electrification scenarios (Reference, -Medium, and High) and three levels of technology advancements (Slow, Moderate, and -Rapid). Load profiles are provided for six separate years: 2018, 2020, 2024, 2030, 2040, -and 2050. The base demand data sets and further accompanying information can be found -[here][nrel_base_dem]. In addition to demand growth projections, NREL has also published -data sets that include hourly profiles for flexible load. These data sets indicate the -amount of demand that is considered to be flexible, as determined through the EFS. The -flexibility demand profiles consider two scenarios of flexibility (Base and Enhanced), -in addition to the classifications for each sector, electrification scenario, technology -advancement, and year. The flexible demand data sets and further accompanying -information can be found [here][nrel_flex_dem]. - -Widespread electrification can have a large impact on future power system planning -decisions and operation. While increased electricity demand can have obvious -implications for generation and transmission capacity planning, new electrified demand -(e.g., electric vehicles, air source heat pumps, and heat pump water heaters) offers -large amounts of potential operational flexibility to grid operators. This flexibility -by demand-side resources can result in demand shifting from times of peak demand to -times of peak renewable generation, presenting the opportunity to defer generation and -transmission capacity upgrades. To help electrification impacts be considered properly, -this package has the ability to access NREL's EFS demand data sets. Currently, users can -access the base demand profiles, allowing the impacts of demand growth due to vast -electrification to be explored. Users can also access the EFS flexible demand profiles, -though integration of demand-side flexibility modeling to the rest of Breakthrough -Energy Sciences' production cost model will be included in a future release. +# PreREISE +**PreREISE** is part of a Python software ecosystem developed by [Breakthrough +Energy Sciences](https://science.breakthroughenergy.org/) to carry out power flow study +in the U.S. electrical grid. -#### I. Downloading and Extracting EFS Demand and Flexibility Data -The EFS demand data sets are stored on the 'NREL Data Catalog' in .zip files. The 'NREL -Data Catalog' contains nine .zip files, one for each combination of electrification -scenario and technology advancement. The ***.csv*** file compressed within the .zip file -contains the sectoral demand for each state and year. This data can be downloaded and -extracted using the following: -```python -from prereise.gather.demanddata.nrel_efs.get_efs_data import download_demand_data -download_demand_data(es, ta, fpath, sz_path) -``` -where `es` is the set of electrification scenarios to be downloaded, `ta` is the set of -technology advancements to be downloaded, `fpath` is the file path to which the NREL EFS -data will be downloaded, and `sz_path` is the file path to which [7-Zip][7zip] is -located for Windows users. `es` and `ta` default to downloading each of the -electrification scenarios and technology advancements, respectively. `fpath` defaults to -downloading the EFS data to the current directory. `sz_path` defaults to the default -installation location for 7-Zip. +## Main Features +**PreREISE** is dedicated to the building of demand, hydro, solar and wind profiles. A detailed presentation of the data source and algorithms used to generate profiles can +be found on our [docs]. -The EFS flexibility data sets are also stored on the 'NREL Data Catalog' in .zip files. -The flexibility data is stored differently from the base demand data, with flexibility -data stored in three separate .zip files, one for each electrification scenario. The -***.csv*** file compressed within the .zip file contains the sectoral flexibility for -each state, year, technology advancement, and flexibility scenario. This data can be -downloaded and extracted using the following: -```python -from prereise.gather.demanddata.nrel_efs.get_efs_data import download_flexibility_data +--- +**NOTE** -download_flexibility_data(es, fpath, sz_path) -``` +Profiles are publicly available for the Breakthrough Energy Sciences (BES) +grid model. Therefore, you don’t need to generate any input data if you use the +scenario framework to carry out power flow study. -where `es` is the set of electrification scenarios to be downloaded, `fpath` is the file -path to which the NREL EFS data will be downloaded, and `sz_path` is the file path to -which 7-Zip is located for Windows users. `es` defaults to downloading each of the -electrification scenarios. `fpath` defaults to downloading the EFS data to the current -directory. `sz_path` defaults to the default installation location for 7-Zip. +--- -Although downloading the .zip files is a simple task, extracting the ***.csv*** files -using Python is more challenging. The .zip files stored on the 'NREL Data Catalog' are -compressed using a compression method (Deflate64, or compression type 9) that is not -currently supported by `zipfile`, a popular Python package for working with .zip files. -To extract the ***.csv*** files in an automated fashion, it is necessary to use either -the Command Prompt or the Terminal, depending on the user's operating system. For -machines running macOS or Linux, the Terminal's extraction tools are capable of -accessing the ***.csv*** file. However, Windows machines are unable to extract the -***.csv*** files using the Command Prompt's extraction tools due to the compression -method. For Windows users with 7-Zip, the ***.csv*** file can be extracted, so long as -7-Zip is installed in the default location. If none of these methods succeed in -extracting the ***.csv*** file, then users can extract the file manually by going to the -.zip file's location and using their extraction tool of choice. For instance, even -though Windows' Command Prompt extraction tools do not work, the native extraction tool -built into Windows' File Explorer does work. -#### II. Splitting the EFS Demand and Flexibility Data by Sector and Year -The EFS demand data for a given electrification scenario and technology advancement is -provided for each sector and each year. Although the sectoral demand is eventually -aggregated for a given year (see next subsection), splitting the demand by sector can be -useful, especially for users that may only want to use a subset of the EFS sectoral -demand (perhaps to pair with their own sectoral demand data). EFS demand data for a -single electrification scenario and technology advancement pair can be split by sector -as follows: -```python -from prereise.gather.demanddata.nrel_efs.get_efs_data import partition_demand_by_sector +## Where to get it +For now, only the source code is available. Clone or Fork the code here on GitHub. -sect_dem = partition_demand_by_sector(es, ta, year, sect, fpath, save) -``` -where `es` is a string describing a single electrification scenario, `ta` is a string -describing a single technology advancement, `year` is an integer describing the included -year, `sect` is a set of the sectors to include, `fpath` is the file path where the -demand data might be located and to where the sectoral demand will be saved (if -desired), and `save` is a boolean that indicates whether the sectoral demand should be -saved. `sect` defaults to including all the sectors (i.e., all sectoral demand is -retained). `fpath` defaults to the current directory. `save` defaults to `False` (i.e., -each sectoral demand DataFrame is not saved). `partition_demand_by_sector` returns -`sect_dem`, which is a dictionary of DataFrames, where each DataFrame contains the -demand data for one sector. -The EFS flexibility data for a given electrification scenario is provided for each -sector, year, technology advancement, and flexibility scenario. It is useful to split -the flexibility data by sector for a specific year, technology advancement, and -flexibility scenario. It is useful to split flexibility data by sector because different -sectors may have different operational constraints (e.g., duration between demand -curtailment and recovery, directionality of load shift). EFS flexibility data can be -split by sector as follows: -```python -from prereise.gather.demanddata.nrel_efs.get_efs_data import partition_flexibility_by_sector +## Dependencies +**PreREISE** relies on: +* **PowerSimData**, another package developed by Breakthrough Energy Sciences and +available [here][PowerSimData]. +* Several Python packages all available on [PyPi](https://pypi.org/) whose list can be +found in the ***requirements.txt*** or ***Pipfile*** files both located at the root of +this package. -sect_dem = partition_flexibility_by_sector(es, ta, flex, year, sect, fpath, save) -``` -where `es` is a string describing a single electrification scenario, `ta` is a string -describing a single technology advancement, flex is a string describing a single -flexibility scenario, `year` is an integer describing the included year, `sect` is a set -of the sectors to include, `fpath` is the file path where the flexibility data might be -located and to where the flexibility demand will be saved (if desired), and `save` is a -boolean that indicates whether the sectoral flexibility data should be saved. `sect` -defaults to including all the sectors (i.e., all sectoral flexibility is retained). -`fpath` defaults to the current directory. `save` defaults to `False` (i.e., each -sectoral flexibility DataFrame is not saved). `partition_flexibility_by_sector` returns -`sect_flex`, which is a dictionary of DataFrames, where each DataFrame contains the -flexibility data for one sector. -`partition_demand_by_sector` and `partition_flexibility_by_sector` check the file path -provided by `fpath` to determine if the data is already downloaded and extracted. If the -data is not present as a ***.csv*** file, then `partition_demand_by_sector` and -`partition_flexibility_by_sector` use `download_demand_data` and -`download_flexibility_data`, respectively, to obtain the specified ***.csv*** file. If -the automated approach is not able to extract the ***.csv*** file, -`partition_demand_by_sector` and `partition_flexibility_by_sector` will exit with an -error, and the user will need to manually use their extraction method of choice (as was -discussed in the prior subsection). If manual extraction is required, the user can -simply run `partition_demand_by_sector` and `partition_flexibility_by_sector` again, -making sure that `fpath` points to the appropriate location where the ***.csv*** file is -saved. +## Installation +Clone **PowerSimData** in a folder adjacent to your clone of **PreREISE** as the +installation of packages depends on files in **PowerSimData**. Then, use the +***requirements.txt*** file (via `pip`) or ***Pipfile*** file (via `pipenv`) to install +third party dependencies. -#### III. Aggregating the Sectoral Demand Data -For use in the grid model developed by Breakthrough Energy Sciences, all sectoral demand -must be aggregated within each location for each hour (i.e., only one demand data point -per location per hour). Thus, the sectoral demand must be aggregated together to obtain -a single demand value for each location and each hour. Aggregating sectoral demand can -be accomplished as follows: -```python -from prereise.gather.demanddata.nrel_efs.aggregate_demand import combine_efs_demand -agg_dem = combine_efs_demand(efs_dem, non_efs_dem, save) -``` -where `efs_dem` is a dictionary of different sectoral demand DataFrames pertaining to -the EFS (this input is intended to be the output of `partition_demand_by_sector`), -`non_efs_dem` is a list of different sectoral demand DataFrames that are independent of -the EFS (this input is intended to be the output of `access_non_efs_demand`, which is -addressed below), and `save` is a string representing the desired file path and file -name to which the aggregated demand will be saved as a ***.csv*** file. Both `efs_dem` -and `non_efs_dem` default to `None`, allowing the user to determine how much sectoral -demand of each type (EFS and non-EFS) they would like to include; note that failing to -specify any sectoral demand will raise an error. `save` defaults to `None`, indicating -that the aggregate demand should not be saved. `combine_efs_demand` returns `agg_dem`, -which is a DataFrame of the aggregate demand data. +## License +[MIT](LICENSE) -The `access_non_efs_demand` function allows sectoral demand that is not associated with -the EFS to be used. `access_non_efs_demand` loads locally-stored sectoral demand data, -checks that it is formatted appropriately, and returns a list of sectoral demand -DataFrames that can be fed into `combine_efs_demand`. Preparing non-EFS sectoral demand -is accomplished as follows: -```python -from prereise.gather.demanddata.nrel_efs.aggregate_demand import access_non_efs_demand -sect_dem = access_non_efs_demand(dem_paths) -``` -where `dem_paths` is a list of file paths that point to the ***.csv*** files of -locally-stored sectoral demand data. `access_non_efs_demand` is intended to be used on -sectoral demand data that is not related to the EFS; all sectoral demand data that is -related to the EFS should be handled using `partition_demand_by_sector`. Note that it -will be incumbent upon the user to account for all sectors when building the aggregate -demand profiles (i.e., users will need to ensure that specific sectors are not excluded -or double-counted). +## Documentation +The official documentation can be found [here][docs]. -#### IV. Mapping the State Demand to the Appropriate Load Zones -For use in the grid model developed by Breakthrough Energy Sciences, the state-level -demand provided by the EFS must be mapped to the appropriate load zones. Breakthrough -Energy Sciences defines distinct load zones for each state. For smaller states that are -completely contained within a single interconnection, the load zone might very well be -equal to the whole state. However, large states (e.g., California and New York), states -that are in multiple interconnections (e.g., Montana and New Mexico), and states with a -combination of these two characteristics (e.g., Texas) may have multiple load zones. -State-level demand is mapped to the various load zones according to the percentage of a -state's population that resides in a particular load zone. This mapping can be -accomplished as follows: -```python -from prereise.gather.demanddata.nrel_efs.map_states import decompose_demand_profile_by_state_to_loadzone -df_lz = decompose_demand_profile_by_state_to_loadzone(df, save) -``` -where `df` is a DataFrame of the hourly demand data for each state in the contiguous -U.S. (intended to be the output of `combine_efs_demand` or the components that are -output from `partition_flexibility_by_sector`) and `save` is a string representing the -desired file path and file name to which the demand will be saved as a ***.csv*** file. -`save` defaults to `None`, indicating that the demand should not be saved. -`decompose_demand_profile_by_state_to_loadzone` returns `df_lz`, which is a DataFrame of -the demand data mapped to each load zone. +## Communication Channels +[Sign up](https://science.breakthroughenergy.org/#get-updates) to our email list and +our Slack workspace to get in touch with us. -#### V. Example of Downloading and Preparing EFS Demand Data -To demonstrate the work flow of these modules, this subsection presents an example of -obtaining the EFS demand data and subsequently preparing it for use in Breakthrough -Energy Sciences' grid model. In this example, EFS demand data under the 'Reference' -electrification scenario and the 'Slow' technology advancement are acquired for the year -2030. After mapping the state-level demand to the different load zones, the aggregate -demand is saved as a ***.csv*** file to the current working directory. This example is -implemented as follows: -```python -from prereise.gather.demanddata.nrel_efs.aggregate_demand import combine_efs_demand -from prereise.gather.demanddata.nrel_efs.get_efs_data import partition_demand_by_sector -from prereise.gather.demanddata.nrel_efs.map_states import decompose_demand_profile_by_state_to_loadzone -sect_dem = partition_demand_by_sector(es="Reference", ta="Slow", year=2030, fpath="") -agg_dem = combine_efs_demand(efs_dem=sect_dem) -agg_dem_lz = decompose_demand_profile_by_state_to_loadzone(df=agg_dem, save="EFS_Demand_Reference_Slow_2030.csv") -``` +## Contributing +All contributions (bug report, documentation, feature development, etc.) are welcome. An +overview on how to contribute to this project can be found in our [Contribution +Guide](https://breakthrough-energy.github.io/docs/dev/contribution_guide.html). -#### VI. Example of Downloading and Preparing EFS Flexibility Data -This subsection presents an example of obtaining the EFS flexibility data and -subsequently preparing it for use in Breakthrough Energy Sciences' grid model. In this -example, EFS flexibility data under the 'Reference' electrification scenario, 'Slow' -technology advancement, and 'Base' flexibility scenario are acquired for the year 2030. -The state-level sectoral flexibility is mapped to the different load zones, however the -different flexibility data are not saved as ***.csv*** files as was done in the prior -example. This example is implemented as follows: -```python -from prereise.gather.demanddata.nrel_efs.get_efs_data import partition_flexibility_by_sector -from prereise.gather.demanddata.nrel_efs.map_states import decompose_demand_profile_by_state_to_loadzone -sect_flex = partition_flexibility_by_sector(es="Reference", ta="Slow", flex="Base", year=2030, fpath="") -sect_flex_lz = {k: decompose_demand_profile_by_state_to_loadzone(df=v) for k, v in sect_flex.items()} -``` -[RAP]: https://www.ncdc.noaa.gov/data-access/model-data/model-datasets/rapid-refresh-rap -[RAP_notebook]: https://github.com/Breakthrough-Energy/PreREISE/blob/develop/prereise/gather/winddata/rap/demo/rap_demo.ipynb -[NetCDF]: https://www.unidata.ucar.edu/software/thredds/current/tds/reference/NetcdfSubsetServiceReference.html -[WIND_doc]: https://www.nrel.gov/docs/fy14osti/61714.pdf -[WIND_web]: https://www.nrel.gov/grid/wind-toolkit.html -[WIND_api]: https://developer.nrel.gov/docs/wind/wind-toolkit/ -[TE_WIND_notebook]: https://github.com/Breakthrough-Energy/PreREISE/blob/develop/prereise/gather/winddata/te_wind/demo/te_wind_demo.ipynb -[NREL_notebooks]: https://github.com/NREL/hsds-examples -[GA_WIND_notebook]: https://github.com/Breakthrough-Energy/PreREISE/blob/develop/prereise/gather/solardata/ga_wind/demo/ga_wind_demo.ipynb -[NSRDB_web]: https://nsrdb.nrel.gov/ -[NSRDB_api]: https://developer.nrel.gov/docs/solar/nsrdb/ -[NSRDB_signup]: https://developer.nrel.gov/signup/ -[SAM_web]: https://sam.nrel.gov/ -[SAM_sdk]: https://sam.nrel.gov/sdk -[SAM_pvwatts]: https://nrel-pysam.readthedocs.io/en/master/modules/Pvwattsv7.html -[NSRDB_naive_notebook]: https://github.com/Breakthrough-Energy/PreREISE/blob/develop/prereise/gather/solardata/nsrdb/demo/nsrdb_naive_demo.ipynb -[NSRDB_sam_notebook]: https://github.com/Breakthrough-Energy/PreREISE/blob/develop/prereise/gather/solardata/nsrdb/demo/nsrdb_sam_demo.ipynb -[hydro_cf]: https://www.eia.gov/electricity/annual/html/epa_04_08_b.html -[hydro_v1_notebook]: https://github.com/Breakthrough-Energy/PreREISE/blob/develop/prereise/gather/hydrodata/eia/demo/hydro_v1_demo.ipynb -[demand_doc]: https://www.eia.gov/realtime_grid/docs/userguide-knownissues.pdf -[demand_notebook]: https://github.com/Breakthrough-Energy/PreREISE/blob/develop/prereise/gather/demanddata/eia/demo/assemble_ba_from_excel_demo.ipynb -[demand_anomaly]: https://github.com/Breakthrough-Energy/PreREISE/blob/develop/prereise/gather/demanddata/eia/demo/ba_anomaly_detection_demo.ipynb -[EIA 923]: https://www.eia.gov/electricity/data/eia923/ -[CAISO_outlook]: http://www.caiso.com/TodaysOutlook/Pages/default.aspx -[hydro_v2_western_notebook]: https://github.com/Breakthrough-Energy/PreREISE/blob/develop/prereise/gather/hydrodata/eia/demo/western_hydro_v2_demo.ipynb -[hydro_v2_texas_notebook]: https://github.com/Breakthrough-Energy/PreREISE/blob/develop/prereise/gather/hydrodata/eia/demo/texas_hydro_v2_demo.ipynb -[eastern_demand_v5_demo]: https://github.com/Breakthrough-Energy/PreREISE/blob/develop/prereise/gather/demanddata/eia/demo/demo_Eastern_v5/eastern_demand_v5_demo.ipynb -[issue #71]: https://github.com/Breakthrough-Energy/PreREISE/issues/71 -[EIA 860]: https://www.eia.gov/electricity/data/eia860/ -[ERCOT_generation]: http://www.ercot.com/gridinfo/generation/ -[USACE_dataquery]: http://www.nwd-wc.usace.army.mil/dd/common/dataquery/www/ -[EIA 930]: https://www.eia.gov/opendata/ -[demand_profiles]: https://github.com/Breakthrough-Energy/PreREISE/blob/develop/docs/demand_profiles.md -[hydro_profiles]: https://github.com/Breakthrough-Energy/PreREISE/blob/develop/docs/hydro_profiles.md -[solar_profiles]: https://github.com/Breakthrough-Energy/PreREISE/blob/develop/docs/solar_profiles.md -[wind_profiles]: https://github.com/Breakthrough-Energy/PreREISE/blob/develop/docs/wind_profiles.md -[ISO New England]: https://www.iso-ne.com/isoexpress/ -[NY ISO]: http://mis.nyiso.com/public/P-63list.htm -[PJM]: http://dataminer2.pjm.com/feed/gen_by_fuel -[Southwest Power Pool]: https://marketplace.spp.org/pages/generation-mix-historical -[hydro_v3_eastern_notebook]: https://github.com/Breakthrough-Energy/PreREISE/blob/develop/prereise/gather/hydrodata/eia/demo/eastern_hydro_v3_demo/eastern_hydro_v3_demo.ipynb -[pumped storage hydro model]: https://github.com/Breakthrough-Energy/PreREISE/blob/develop/prereise/gather/hydrodata/eia/demo/eastern_hydro_v3_demo/hps_plants_eastern.xlsx -[nrel_efs]: https://www.nrel.gov/analysis/electrification-futures.html -[nrel_base_dem]: https://data.nrel.gov/submissions/126 -[nrel_flex_dem]: https://data.nrel.gov/submissions/127 -[7zip]: https://www.7-zip.org/ +[docs]: https://breakthrough-energy.github.io/docs/index.html +[PowerSimData]: https://github.com/Breakthrough-Energy/PowerSimData From d92b98737f0de9c09c478debb7b2bc34bebfa9ac Mon Sep 17 00:00:00 2001 From: BainanXia Date: Mon, 2 Aug 2021 16:46:39 -0500 Subject: [PATCH 40/61] data: update BA_County_map.json to eliminate duplicate assignments --- prereise/gather/data/BA_County_map.json | 12 +----------- 1 file changed, 1 insertion(+), 11 deletions(-) diff --git a/prereise/gather/data/BA_County_map.json b/prereise/gather/data/BA_County_map.json index eee98380d..0fbd07a7c 100644 --- a/prereise/gather/data/BA_County_map.json +++ b/prereise/gather/data/BA_County_map.json @@ -2113,7 +2113,6 @@ "WAUE": [ "Pembina__ND", "Kimball__NE", - "Laramie__WY", "Yankton__SD", "Sioux__NE", "Aurora__SD", @@ -2189,7 +2188,6 @@ "Henry/Rives__MO", "St. Clair__MO", "Cass/Van Buren__MO", - "Laclede__MO", "Carroll__MO", "Livingston__MO", "Johnson__KS", @@ -2198,12 +2196,10 @@ "Chariton__MO", "Saline__MO", "Webster__MO", - "Douglas__MO", "Grundy__MO", "Harrison__MO", "Mercer__MO", "Sullivan__MO", - "Wright__MO", "Franklin__KS", "Leavenworth__KS", "Cass__MO", @@ -2649,7 +2645,6 @@ "Lake__OR", "Grant__OR", "Wheeler__OR", - "Malheur__OR", "Linn__OR", "Columbia__OR", "Jefferson__OR", @@ -2706,7 +2701,6 @@ "San Miguel__NM", "Santa Fe__NM", "Hidalgo__NM", - "Union__NM", "Harding__NM", "Sierra__NM", "Taos__NM", @@ -2716,17 +2710,13 @@ "Grant__NM", "Catron__NM", "McKinley__NM", - "Quay__NM", "Bernalillo__NM", "Torrance__NM", "Colfax__NM", "Lincoln__NM", "Valencia__NM", "Mora__NM", - "Socorro__NM", - "Lea__NM", - "Roosevelt__NM", - "Curry__NM" + "Socorro__NM" ], "PACE": [ "San Juan__UT", From 3cba64048dfaff10b31f81084065fb35845f7494 Mon Sep 17 00:00:00 2001 From: BainanXia Date: Mon, 2 Aug 2021 17:04:58 -0500 Subject: [PATCH 41/61] data: update all_bus_ba_map.csv to reflect the change in BA_County_map.json --- prereise/gather/data/all_bus_ba_map.csv | 294 ++++++++++++------------ 1 file changed, 147 insertions(+), 147 deletions(-) diff --git a/prereise/gather/data/all_bus_ba_map.csv b/prereise/gather/data/all_bus_ba_map.csv index 90d9e94fe..3b9c36eee 100644 --- a/prereise/gather/data/all_bus_ba_map.csv +++ b/prereise/gather/data/all_bus_ba_map.csv @@ -55581,16 +55581,16 @@ bus_id,lat,lon,County,BA 55580,38.1391,-92.6871,Camden__MO,LRZ3_5 55581,38.1391,-92.6871,Camden__MO,LRZ3_5 55582,38.2213,-92.6979,Camden__MO,LRZ3_5 -55583,37.7677,-92.6682,Laclede__MO,KCPL_INDN -55584,37.7677,-92.6682,Laclede__MO,KCPL_INDN -55585,37.7677,-92.6682,Laclede__MO,KCPL_INDN -55586,37.7677,-92.6682,Laclede__MO,KCPL_INDN -55587,37.7677,-92.6682,Laclede__MO,KCPL_INDN -55588,37.6782,-92.6402,Laclede__MO,KCPL_INDN -55589,37.6402,-92.6285,Laclede__MO,KCPL_INDN -55590,37.6402,-92.6285,Laclede__MO,KCPL_INDN -55591,37.6402,-92.6285,Laclede__MO,KCPL_INDN -55592,37.6269,-92.6594,Laclede__MO,KCPL_INDN +55583,37.7677,-92.6682,Laclede__MO,AECI +55584,37.7677,-92.6682,Laclede__MO,AECI +55585,37.7677,-92.6682,Laclede__MO,AECI +55586,37.7677,-92.6682,Laclede__MO,AECI +55587,37.7677,-92.6682,Laclede__MO,AECI +55588,37.6782,-92.6402,Laclede__MO,AECI +55589,37.6402,-92.6285,Laclede__MO,AECI +55590,37.6402,-92.6285,Laclede__MO,AECI +55591,37.6402,-92.6285,Laclede__MO,AECI +55592,37.6269,-92.6594,Laclede__MO,AECI 55593,37.9564,-92.5976,Camden__MO,LRZ3_5 55594,37.9564,-92.5976,Camden__MO,LRZ3_5 55595,37.9564,-92.5976,Camden__MO,LRZ3_5 @@ -55752,15 +55752,15 @@ bus_id,lat,lon,County,BA 55751,37.9421,-91.7854,Phelps__MO,AECI 55752,37.9421,-91.7854,Phelps__MO,AECI 55753,37.9421,-91.7854,Phelps__MO,AECI -55754,36.9957,-92.5866,Douglas__MO,KCPL_INDN -55755,36.9957,-92.5866,Douglas__MO,KCPL_INDN -55756,36.9957,-92.5866,Douglas__MO,KCPL_INDN -55757,36.9957,-92.5866,Douglas__MO,KCPL_INDN -55758,36.9957,-92.5866,Douglas__MO,KCPL_INDN -55759,36.8081,-92.7027,Douglas__MO,KCPL_INDN -55760,36.8081,-92.7027,Douglas__MO,KCPL_INDN -55761,36.8081,-92.7027,Douglas__MO,KCPL_INDN -55762,36.853,-92.7507,Douglas__MO,KCPL_INDN +55754,36.9957,-92.5866,Douglas__MO,AECI +55755,36.9957,-92.5866,Douglas__MO,AECI +55756,36.9957,-92.5866,Douglas__MO,AECI +55757,36.9957,-92.5866,Douglas__MO,AECI +55758,36.9957,-92.5866,Douglas__MO,AECI +55759,36.8081,-92.7027,Douglas__MO,AECI 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+62005,34.9569,-103.399,Quay__NM,SPS +62006,34.9569,-103.399,Quay__NM,SPS +62007,32.728,-103.3,Lea__NM,SPS +62008,32.728,-103.3,Lea__NM,SPS +62009,32.728,-103.3,Lea__NM,SPS +62010,32.728,-103.3,Lea__NM,SPS +62011,32.728,-103.3,Lea__NM,SPS +62012,32.6767,-103.322,Lea__NM,SPS +62013,32.6767,-103.322,Lea__NM,SPS +62014,32.7283,-103.286,Lea__NM,SPS +62015,32.7283,-103.286,Lea__NM,SPS +62016,32.7283,-103.286,Lea__NM,SPS 62017,36.2456,-94.6645,Delaware__OK,GRDA 62018,36.2296,-94.7266,Delaware__OK,GRDA 62019,36.314,-94.7624,Delaware__OK,GRDA From 833e752d8db3f5695aea3bc2f389fd2b2475d31f Mon Sep 17 00:00:00 2001 From: jon-hagg <66005238+jon-hagg@users.noreply.github.com> Date: Thu, 26 Aug 2021 10:58:26 -0700 Subject: [PATCH 42/61] Update dependencies (#209) Co-authored-by: jon-hagg --- Pipfile.lock | 593 ++++++++++++++++++++++++++++----------------------- 1 file changed, 329 insertions(+), 264 deletions(-) diff --git a/Pipfile.lock b/Pipfile.lock index c0dcb505e..5e76ac608 100644 --- a/Pipfile.lock +++ b/Pipfile.lock @@ -21,6 +21,13 @@ ], "version": "==1.2.7" }, + "appdirs": { + "hashes": [ + "sha256:7d5d0167b2b1ba821647616af46a749d1c653740dd0d2415100fe26e27afdf41", + "sha256:a841dacd6b99318a741b166adb07e19ee71a274450e68237b4650ca1055ab128" + ], + "version": "==1.4.4" + }, "bcrypt": { "hashes": [ "sha256:5b93c1726e50a93a033c36e5ca7fdcd29a5c7395af50a6892f5d9e7c6cfbfb29", @@ -67,8 +74,10 @@ "sha256:3c8d896becff2fa653dc4438b54a5a25a971d1f4110b32bd3068db3722c80202", "sha256:4373612d59c404baeb7cbd788a18b2b2a8331abcc84c3ba40051fcd18b17a4d5", "sha256:487d63e1454627c8e47dd230025780e91869cfba4c753a74fda196a1f6ad6548", + "sha256:48916e459c54c4a70e52745639f1db524542140433599e13911b2f329834276a", "sha256:4922cd707b25e623b902c86188aca466d3620892db76c0bdd7b99a3d5e61d35f", "sha256:55af55e32ae468e9946f741a5d51f9896da6b9bf0bbdd326843fec05c730eb20", + "sha256:57e555a9feb4a8460415f1aac331a2dc833b1115284f7ded7278b54afc5bd218", 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], + "version": "==2021.8.21" }, "toml": { "hashes": [ @@ -1119,6 +1176,14 @@ ], "markers": "python_version >= '2.6' and python_version not in '3.0, 3.1, 3.2, 3.3'", "version": "==0.10.2" + }, + "tomli": { + "hashes": [ + "sha256:8dd0e9524d6f386271a36b41dbf6c57d8e32fd96fd22b6584679dc569d20899f", + "sha256:a5b75cb6f3968abb47af1b40c1819dc519ea82bcc065776a866e8d74c5ca9442" + ], + "markers": "python_version >= '3.6'", + "version": "==1.2.1" } } } From 2dec5377b611627b90746b05291c45ab36792fa2 Mon Sep 17 00:00:00 2001 From: jon-hagg <66005238+jon-hagg@users.noreply.github.com> Date: Wed, 1 Sep 2021 17:11:59 -0700 Subject: [PATCH 43/61] ci: replace docs trigger with generic one (#211) --- .github/workflows/docs-trigger.yml | 14 -------------- .github/workflows/external.yml | 18 ++++++++++++++++++ 2 files changed, 18 insertions(+), 14 deletions(-) delete mode 100644 .github/workflows/docs-trigger.yml create mode 100644 .github/workflows/external.yml diff --git a/.github/workflows/docs-trigger.yml b/.github/workflows/docs-trigger.yml deleted file mode 100644 index 5c626d9bf..000000000 --- a/.github/workflows/docs-trigger.yml +++ /dev/null @@ -1,14 +0,0 @@ -name: Update docs - -on: - push: - branches: - - develop - -jobs: - dispatch: - runs-on: ubuntu-latest - steps: - - uses: Breakthrough-Energy/actions/publish-docs@main - with: - token: ${{ secrets.CI_TOKEN_CLONE_REPO }} diff --git a/.github/workflows/external.yml b/.github/workflows/external.yml new file mode 100644 index 000000000..5ca673e78 --- /dev/null +++ b/.github/workflows/external.yml @@ -0,0 +1,18 @@ +name: Trigger external workflows + +on: + push: + branches: + - develop + +jobs: + run-workflows: + runs-on: ubuntu-latest + steps: + - name: Build and publish docs website + uses: Breakthrough-Energy/actions/workflow-trigger@main + with: + repo: docs + branch: master + workflow_id: 2386877 + token: ${{ secrets.CI_TOKEN_CLONE_REPO }} From 2e1ce52dc0c4d00124c4eec85eb9420fd1a18ce6 Mon Sep 17 00:00:00 2001 From: Jon Hagg Date: Thu, 2 Sep 2021 16:24:51 -0700 Subject: [PATCH 44/61] chore: switch to setup.cfg and pin powersimdata version --- Pipfile | 2 +- Pipfile.lock | 393 +++++++++++++++++++++++++---------------------- requirements.txt | 2 +- setup.cfg | 25 +++ setup.py | 19 +-- 5 files changed, 235 insertions(+), 206 deletions(-) create mode 100644 setup.cfg diff --git a/Pipfile b/Pipfile index df2778db9..6d1df5161 100644 --- a/Pipfile +++ b/Pipfile @@ -21,6 +21,6 @@ scipy = "~=1.6" tqdm = "==4.29.1" xlrd = "==1.2.0" netCDF4 = "==1.5.4" -powersimdata = {editable = true, path = "../PowerSimData"} +powersimdata = "~=0.4.4" nrel-pysam = "~=2.2" pyproj = "==2.6.1.post1" diff --git a/Pipfile.lock b/Pipfile.lock index 5e76ac608..f70ad59b3 100644 --- a/Pipfile.lock +++ b/Pipfile.lock @@ -1,7 +1,7 @@ { "_meta": { "hash": { - "sha256": "150ca8d367ec2dddcb9b8cc69d537b748407f19e87c55f8d579d8d099059975b" + "sha256": "c6bf0147eb1cbbe885779e8d4d1fbdecd1c7d64dcc681c677aea54622a77e830" }, "pipfile-spec": 6, "requires": {}, @@ -210,19 +210,19 @@ }, "google-api-core": { "hashes": [ - "sha256:428805de17b48ca1af2fdb5bbfc2334e1bbcb0ea4a16506fa1337fb29c8f37c8", - "sha256:bd9eb0709f4e10dd6fddb32fd0788a190b434426c258be6e00ef40da136d768d" + "sha256:b8ad41f72a70dd709dd13a08478936172aecf5f2d34a18ab378efa6d2d6ab575", + "sha256:d6760f21b3a064a8397916b33be7383fc169d1a3c3d7fae7b47eb92bba7892b8" ], "markers": "python_version >= '3.6'", - "version": "==2.0.0" + "version": "==2.0.1" }, "google-api-python-client": { "hashes": [ - "sha256:6e990fc4d0419c2011f75ca5c2762efbb7eb4def67bbe2f1b98a8ccb73117bf5", - "sha256:a25661ec6cf4c159f41fe9c061c2bee31b2dddaf2ad787e23617048a25b53842" + "sha256:1f2657d1be246bc3d4bd1f0642f498653ce5fba507e6a05bbc405ed65bf10377", + "sha256:c89b345615188fbd525f52d59013156ad3bfd1023af27041f2dec3d7877ba112" ], "markers": "python_version >= '3.6'", - "version": "==2.18.0" + "version": "==2.19.1" }, 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"sha256:806143ae5bfb6a3c6e736a764057db0e6a0e05e338b5630894a5f779cabb4f9b", "sha256:b3bda1d108d5dd99f4a20d24d9c348e91c4db7ab1b749200bded2f839ccbe68f" ], - "markers": "python_version >= '2.6' and python_version not in '3.0, 3.1, 3.2, 3.3'", + "markers": "python_version >= '2.6' and python_version not in '3.0, 3.1, 3.2'", "version": "==0.10.2" }, "tomli": { @@ -1184,6 +1195,14 @@ ], "markers": "python_version >= '3.6'", "version": "==1.2.1" + }, + "typing-extensions": { + "hashes": [ + "sha256:49f75d16ff11f1cd258e1b988ccff82a3ca5570217d7ad8c5f48205dd99a677e", + "sha256:d8226d10bc02a29bcc81df19a26e56a9647f8b0a6d4a83924139f4a8b01f17b7", + "sha256:f1d25edafde516b146ecd0613dabcc61409817af4766fbbcfb8d1ad4ec441a34" + ], + "version": "==3.10.0.2" } } } diff --git a/requirements.txt b/requirements.txt index 015fbda4a..76b1ad139 100644 --- a/requirements.txt +++ b/requirements.txt @@ -4,7 +4,7 @@ matplotlib~=3.3 netCDF4==1.5.4 numpy~=1.20 pandas~=1.1.2 --e ../PowerSimData +powersimdata~=0.4.4 pyproj==2.6.1.post1 python-dateutil==2.7.5 requests~=2.25 diff --git a/setup.cfg b/setup.cfg new file mode 100644 index 000000000..1726a0e7e --- /dev/null +++ b/setup.cfg @@ -0,0 +1,25 @@ +[metadata] +name = prereise +version = 0.4 +author = Kaspar Mueller +author_email = kaspar@breakthroughenergy.org +description = Create and run an energy scenario +long_description = file: README.md +long_description_content_type = text/markdown +url = https://github.com/Breakthrough-Energy/PreREISE +project_urls = + Bug Tracker = https://github.com/Breakthrough-Energy/PreREISE/issues +classifiers = + License :: OSI Approved :: MIT License + Operating System :: OS Independent + Programming Language :: Python :: 3 + Programming Language :: Python :: 3.7 + Programming Language :: Python :: 3.8 + +[options] +zip_safe = False +packages = find: +python_requires = >=3.7 + +[options.package_data] +prereise = gather/*/data/*, gather/data/* diff --git a/setup.py b/setup.py index 4be9c82ac..606849326 100644 --- a/setup.py +++ b/setup.py @@ -1,18 +1,3 @@ -from setuptools import find_packages, setup +from setuptools import setup -setup( - name="prereise", - version="0.4", - description="Create and run an energy scenario", - url="https://github.com/Breakthrough-Energy/PreREISE", - author="Kaspar Mueller", - author_email="kaspar@breakthroughenergy.org", - packages=find_packages(), - package_data={ - "prereise": [ - "gather/*/data/*", - "gather/data/*", - ] - }, - zip_safe=False, -) +setup() From 14742401577fe820364f45b0753d745d1e9ba132 Mon Sep 17 00:00:00 2001 From: Jon Hagg Date: Fri, 3 Sep 2021 12:52:01 -0700 Subject: [PATCH 45/61] ci: remove unnecessary clone step --- .github/workflows/coverage.yml | 15 +-------------- .github/workflows/packages.yml | 14 +------------- .github/workflows/test.yml | 14 +------------- 3 files changed, 3 insertions(+), 40 deletions(-) diff --git a/.github/workflows/coverage.yml b/.github/workflows/coverage.yml index 98711d79b..425b119cd 100644 --- a/.github/workflows/coverage.yml +++ b/.github/workflows/coverage.yml @@ -11,16 +11,7 @@ jobs: name: Generate coverage report steps: - - name: Checkout PreREISE - uses: actions/checkout@v2 - with: - path: PreREISE - - - name: Checkout PowerSimData - uses: actions/checkout@v2 - with: - repository: Breakthrough-Energy/PowerSimData - path: PowerSimData + - uses: actions/checkout@v2 - name: Set up Python uses: actions/setup-python@v2 @@ -28,14 +19,10 @@ jobs: python-version: 3.8 - run: python -m pip install --upgrade pip tox - working-directory: PreREISE - - run: tox -e pytest-local -- --cov-report=xml - working-directory: PreREISE - name: Upload coverage to Codecov uses: codecov/codecov-action@v1 with: name: codecov-prereise fail_ci_if_error: true - directory: PreREISE diff --git a/.github/workflows/packages.yml b/.github/workflows/packages.yml index 263d3ae8f..36f928e00 100644 --- a/.github/workflows/packages.yml +++ b/.github/workflows/packages.yml @@ -8,22 +8,11 @@ jobs: runs-on: ubuntu-latest steps: - - name: Checkout PreREISE - uses: actions/checkout@v2 - with: - path: PreREISE - - - name: Checkout PowerSimData - uses: actions/checkout@v2 - with: - repository: Breakthrough-Energy/PowerSimData - path: PowerSimData + - uses: actions/checkout@v2 - name: Pipenv lock id: pipenv_lock uses: Breakthrough-Energy/actions/update-packages@main - with: - repo-dir: PreREISE - name: Parse JSON id: parse_json @@ -68,4 +57,3 @@ jobs: [1]: https://github.com/peter-evans/create-pull-request branch: update-dependencies - path: PreREISE diff --git a/.github/workflows/test.yml b/.github/workflows/test.yml index 0fbe2aa23..11ea2d03f 100644 --- a/.github/workflows/test.yml +++ b/.github/workflows/test.yml @@ -18,16 +18,7 @@ jobs: name: Python ${{ matrix.python-version }} steps: - - name: Checkout PreREISE - uses: actions/checkout@v2 - with: - path: PreREISE - - - name: Checkout PowerSimData - uses: actions/checkout@v2 - with: - repository: Breakthrough-Energy/PowerSimData - path: PowerSimData + - uses: actions/checkout@v2 - name: Set up Python ${{ matrix.python-version }} uses: actions/setup-python@v2 @@ -35,7 +26,4 @@ jobs: python-version: ${{ matrix.python-version }} - run: python -m pip install --upgrade tox - working-directory: PreREISE - - run: tox -e pytest-local - working-directory: PreREISE From e8fab4313f257bf890a2a4daaf9b0e9fae3adeb3 Mon Sep 17 00:00:00 2001 From: George Tong Date: Mon, 13 Sep 2021 13:47:11 -0700 Subject: [PATCH 46/61] feat: add ability to download hrrr data (#212) --- prereise/gather/winddata/hrrr/__init__.py | 0 prereise/gather/winddata/hrrr/constants.py | 6 + prereise/gather/winddata/hrrr/downloader.py | 20 +++ prereise/gather/winddata/hrrr/grib.py | 105 ++++++++++++++++ prereise/gather/winddata/hrrr/helpers.py | 30 +++++ prereise/gather/winddata/hrrr/hrrr.py | 20 +++ prereise/gather/winddata/hrrr/hrrr_api.py | 115 ++++++++++++++++++ .../gather/winddata/hrrr/tests/__init__.py | 0 .../gather/winddata/hrrr/tests/test_grib.py | 73 +++++++++++ .../winddata/hrrr/tests/test_helpers.py | 13 ++ .../winddata/hrrr/tests/test_hrrr_api.py | 94 ++++++++++++++ 11 files changed, 476 insertions(+) create mode 100644 prereise/gather/winddata/hrrr/__init__.py create mode 100644 prereise/gather/winddata/hrrr/constants.py create mode 100644 prereise/gather/winddata/hrrr/downloader.py create mode 100644 prereise/gather/winddata/hrrr/grib.py create mode 100644 prereise/gather/winddata/hrrr/helpers.py create mode 100644 prereise/gather/winddata/hrrr/hrrr.py create mode 100644 prereise/gather/winddata/hrrr/hrrr_api.py create mode 100644 prereise/gather/winddata/hrrr/tests/__init__.py create mode 100644 prereise/gather/winddata/hrrr/tests/test_grib.py create mode 100644 prereise/gather/winddata/hrrr/tests/test_helpers.py create mode 100644 prereise/gather/winddata/hrrr/tests/test_hrrr_api.py diff --git a/prereise/gather/winddata/hrrr/__init__.py b/prereise/gather/winddata/hrrr/__init__.py new file mode 100644 index 000000000..e69de29bb diff --git a/prereise/gather/winddata/hrrr/constants.py b/prereise/gather/winddata/hrrr/constants.py new file mode 100644 index 000000000..3222e5160 --- /dev/null +++ b/prereise/gather/winddata/hrrr/constants.py @@ -0,0 +1,6 @@ +# additional sources of data can be found at https://rapidrefresh.noaa.gov/hrrr/ +# as well as https://github.com/blaylockbk/Herbie/blob/a20d1017ea4c73916cb4436ad797804854109db3/herbie/models/hrrr.py#L58-L63 +HRRR_S3_BASE_URL = "https://noaa-hrrr-bdp-pds.s3.amazonaws.com/hrrr.{dt:%Y%m%d}/conus/hrrr.t{dt:%H}z.wrf{product}f{hours_forecasted:02d}.grib2" +HRRR_GOOGLE_BASE_URL = "https://storage.googleapis.com/high-resolution-rapid-refresh/hrrr.{dt:%Y%m%d}/conus/hrrr.t{dt:%Y%m%d}z.wrf{product}f{hours_forecasted:02d}.grib2" +HRRR_AZURE_BASE_URL = "https://noaahrrr.blob.core.windows.net/hrrr/hrrr.{dt:%Y%m%d}/conus/hrrr.t{dt:%H}z.wrf{product}f{hours_forecasted:02d}.grib2" +HRRR_NOMADS_BASE_URL = "https://nomads.ncep.noaa.gov/pub/data/nccf/com/hrrr/prod/hrrr.{dt:%Y%m%d}/conus/hrrr.t{dt:%H}z.wrf{product}f{hours_forecasted:02d}.grib2" diff --git a/prereise/gather/winddata/hrrr/downloader.py b/prereise/gather/winddata/hrrr/downloader.py new file mode 100644 index 000000000..e0f934bf7 --- /dev/null +++ b/prereise/gather/winddata/hrrr/downloader.py @@ -0,0 +1,20 @@ +import shutil + +import requests + + +class Downloader: + """Class that holds downloading functionality""" + + @staticmethod + def download(url, file, headers): + """Downloads file from a url and stores contents into file. + + :param str url: url to download from + :param io.BufferedIOBase file: file to write to, opened in + binary mode + :param dict headers: dictionary holding headers to be sent + to url when attempting to download + """ + with requests.get(url, stream=True, headers=headers) as r: + shutil.copyfileobj(r.raw, file) diff --git a/prereise/gather/winddata/hrrr/grib.py b/prereise/gather/winddata/hrrr/grib.py new file mode 100644 index 000000000..27481186e --- /dev/null +++ b/prereise/gather/winddata/hrrr/grib.py @@ -0,0 +1,105 @@ +from dataclasses import dataclass + + +@dataclass +class GribRecordInfo: + """Class to hold metadata on a GRIB record. GRIB (General Regularly-distributed + Information in Binary) is a concise data format commonly used in meteorology to + store historical and forecast weather data. GRIB files can have corresponding + index files that holds metadata about the data inside GRIB files. More info + on index files can be found at + `this link `_ + + :param str message_number: message number of the GRIB record + :param str beginning_byte: byte that the GRIB record starts at + :param str ending_byte: byte that the GRIB record ends at. If None + then ending_byte is the end of file + :param str initialization_date: date and hour that the data is for + :param str variable: string designating what kind of data + :param str level: additional string that designates more information about + type of data + :param str forecast: designates how many hours into the future + this data is forecasted for + """ + + message_number: str + beginning_byte: str + ending_byte: str + initialization_date: str + variable: str + level: str + forecast: str + + @classmethod + def from_string(cls, raw_string, next_raw_string=None): + """Creates a GribRecordInfo object from a specific string. + Information on the string format can be found at + `this link `_ + + :param str raw_string: a record line following the format + MESSAGE_NUMBER:BEGINNING_BYTE:INITIALIZATION_DATE:VARIABLE:LEVEL:FORECAST + :param str next_raw_string: the following record line. This + is needed to know when the next record starts, so we know where + the current record ends. + + :return: (*GribRecordInfo*) + """ + details = raw_string.split(":") + assert len(details) >= 6 + ending_byte = None + if next_raw_string: + ending_byte = str(int(next_raw_string.split(":")[1]) - 1) + return cls( + message_number=details[0], + beginning_byte=details[1], + ending_byte=ending_byte, + initialization_date=details[2], + variable=details[3], + level=details[4], + forecast=details[5], + ) + + @classmethod + def generate_grib_record_information_list( + cls, raw_record_information_list, index_list + ): + """Creates a list of GribRecordInfo objects from a + list of raw strings and a list of integers that designate + which raw strings to use to create GribRecordInfo objects. + + :param list raw_record_information_list: a list of record lines that + follow the format: + MESSAGE_NUMBER:BEGINNING_BYTE:INITIALIZATION_DATE:VARIABLE:LEVEL:FORECAST + :param list index_list: a list of integers representing indices + to index into raw_record_information_list to create + GribRecordInfo objects out of + + :return: (*list*) -- a list of GribRecordInfo objects + """ + duplicate_list = raw_record_information_list[:] + duplicate_list.append(None) + return [ + cls.from_string(duplicate_list[ind], duplicate_list[ind + 1]) + for ind in index_list + ] + + def byte_range_header_string(self): + """Returns a string providing the range of + the byte that the record starts at to the byte that the record + ends at. + + :return: (*str*) + """ + return ( + f"{self.beginning_byte}-{self.ending_byte}" + if self.ending_byte + else f"{self.beginning_byte}-" + ) + + @classmethod + def full_file(cls): + """Creates a GribRecordInfo that represents a whole file + + :return: (*GribRecordInfo*) -- a GribRecordInfo representing a whole file + """ + return cls(0, 0, None, None, None, None, None) diff --git a/prereise/gather/winddata/hrrr/helpers.py b/prereise/gather/winddata/hrrr/helpers.py new file mode 100644 index 000000000..20da796cc --- /dev/null +++ b/prereise/gather/winddata/hrrr/helpers.py @@ -0,0 +1,30 @@ +def formatted_filename(dt, product, hours_forecasted): + """Deterministically returns a grib filename + + :param datetime.datetime dt: datetime associated with + the data being stored + :param string product: product associated with the + data being stored + :param string hours_forecasted: how many hours into + the future the data is forecasted + + :return: (*str*) -- a filename + """ + return f"{dt.strftime('%Y_%m_%d_%Hhr')}_{product}_{hours_forecasted}.grib2" + + +def get_indices_that_contain_selector(input_list, selectors): + """Generates list of indices of strings in input_list that + contain a string inside of selectors + + :param list input_list: list of strings + :param list selectors: list of strings + + :return: (*list*) -- list of indices of strings in input_list + that contain a string inside of selectors + """ + return [ + i + for i, item in enumerate(input_list) + if any([selector in item for selector in selectors]) + ] diff --git a/prereise/gather/winddata/hrrr/hrrr.py b/prereise/gather/winddata/hrrr/hrrr.py new file mode 100644 index 000000000..58ce7104f --- /dev/null +++ b/prereise/gather/winddata/hrrr/hrrr.py @@ -0,0 +1,20 @@ +from prereise.gather.winddata.hrrr.constants import HRRR_S3_BASE_URL +from prereise.gather.winddata.hrrr.downloader import Downloader +from prereise.gather.winddata.hrrr.hrrr_api import HrrrApi + + +def retrieve_data(start_dt, end_dt, directory): + """Retrieves all HRRR wind data for all hours between start_dt and + end_dt. (In a future PR) will convert all that wind data to + Pout in order to be compatible with REISE. + + Sample usage: + from datetime import datetime, timedelta + retrieve_data(start_dt=datetime.fromisoformat("2016-01-01"), end_dt=datetime.fromisoformat("2016-01-01") + timedelta(hours=2), directory="./") + + :param datetime.datetime start_dt: datetime to start at + :param datetime.datetime end_dt: datetime to end at + :param str directory: file directory to download data into + """ + api = HrrrApi(Downloader, HRRR_S3_BASE_URL) + api.download_wind_data(start_dt, end_dt, directory) diff --git a/prereise/gather/winddata/hrrr/hrrr_api.py b/prereise/gather/winddata/hrrr/hrrr_api.py new file mode 100644 index 000000000..2bad8c631 --- /dev/null +++ b/prereise/gather/winddata/hrrr/hrrr_api.py @@ -0,0 +1,115 @@ +import requests +from pandas import date_range + +from prereise.gather.winddata.hrrr.grib import GribRecordInfo +from prereise.gather.winddata.hrrr.helpers import ( + formatted_filename, + get_indices_that_contain_selector, +) + + +class HrrrApi: + """Class to interact with to get and download HRRR data. More information + about HRRR data can be found at + `this link `_ + and + `this link `_ + + :param prereise.gather.winddata.hrrr.downloader.Downloader downloader: class + that holds helper functions for downloading + :param str base_url: url to download data from. Should take "dt", "product" + and "hours_forecasted" as format variables. See + :mod:`prereise.gather.winddata.hrrr.constants` for more detail + """ + + U_COMPONENT_FILTER = "UGRD:80 m above ground" + V_COMPONENT_FILTER = "VGRD:80 m above ground" + + def __init__(self, downloader, base_url): + self.downloader = downloader + self.base_url = base_url + + def _filename_url_iter(self, start_dt, end_dt, product): + """Iterates from a start datetime (inclusive) to a end datetime (inclusive) + at 1 hour steps, returning a filename as well as a url based + on each intermediary datetime + + :param datetime.datetime start_dt: datetime to start at + :param datetime.datetime end_dt: datetime to end at + :param str product: info at `this link `_ + + :return: (*generator*) -- generator that yields filename and url + """ + for dt in date_range(start=start_dt, end=end_dt, freq="H").to_pydatetime(): + url = self.base_url.format(dt=dt, product=product, hours_forecasted=0) + yield formatted_filename(dt, product, hours_forecasted=0), url + + def download_meteorological_data( + self, start_dt, end_dt, directory, product, selectors=None + ): + """Iterates from a start datetime (inclusive) to a end datetime (inclusive) + at 1 hour steps, downloading data for each intermediary datetime into + the directory provided. product and selectors variables are used + to control what specific type of data to download. See + `this link `_ to understand + more about product and + `this link `_ + to understand more about what kind of strings can be passed into selectors + + :param datetime.datetime start_dt: datetime to start at + :param datetime.datetime end_dt: datetime to end at + :param str directory: file directory to download data into + :param str product: info at `this link `_ + :param list selectors: list of strings that can be used to narrow down + the amount of data downloaded from a specific GRIB file. + """ + for filename, url in self._filename_url_iter(start_dt, end_dt, product): + grib_record_information_list = [GribRecordInfo.full_file()] + # first grab index file and figure out which bytes to download + if selectors: + index_url = f"{url}.idx" + response = requests.get( + index_url + ) # index files are typically a few kb, so safe to hold in memory + raw_record_information_list = response.text.split("\n") + index_list = get_indices_that_contain_selector( + raw_record_information_list, selectors + ) + grib_record_information_list = ( + GribRecordInfo.generate_grib_record_information_list( + raw_record_information_list, index_list + ) + ) + + with open(directory + filename, "ab") as f: + for grib_record_information in grib_record_information_list: + try: + self.downloader.download( + url, + f, + headers={ + "Range": f"bytes={grib_record_information.byte_range_header_string()}" + }, + ) + except Exception: + print( + f"Failed to download data from {url} with byte range {grib_record_information.byte_range_header_string()}" + ) + + def download_wind_data(self, start_dt, end_dt, directory): + """See :meth:`download_meteorological_data` + for more information. Default product used is "sfc" which represents + 2D Surface Levels, and the selectors used filter specifically for + U component and V component of wind at 80 meters above ground. + + :param datetime.datetime start_dt: datetime to start at + :param datetime.datetime end_dt: datetime to end at + :param str directory: file directory to download data into + """ + self.download_meteorological_data( + start_dt, + end_dt, + directory, + product="sfc", + selectors=[self.U_COMPONENT_FILTER, self.V_COMPONENT_FILTER], + ) diff --git a/prereise/gather/winddata/hrrr/tests/__init__.py b/prereise/gather/winddata/hrrr/tests/__init__.py new file mode 100644 index 000000000..e69de29bb diff --git a/prereise/gather/winddata/hrrr/tests/test_grib.py b/prereise/gather/winddata/hrrr/tests/test_grib.py new file mode 100644 index 000000000..29fb51288 --- /dev/null +++ b/prereise/gather/winddata/hrrr/tests/test_grib.py @@ -0,0 +1,73 @@ +from prereise.gather.winddata.hrrr.grib import GribRecordInfo + +GRIB_RECORD_INFO_ARRAY = [ + "52:38983378:d=2016010121:UGRD:10 m above ground:anl:", + "53:40192462:d=2016010121:VGRD:10 m above ground:anl:", +] + + +def test_grib_info_from_string(): + g = GribRecordInfo.from_string(GRIB_RECORD_INFO_ARRAY[0]) + expected = GribRecordInfo( + message_number="52", + beginning_byte="38983378", + ending_byte=None, + initialization_date="d=2016010121", + variable="UGRD", + level="10 m above ground", + forecast="anl", + ) + assert g == expected + + +def test_grib_info_from_string_with_next_string(): + g = GribRecordInfo.from_string(*GRIB_RECORD_INFO_ARRAY) + expected = GribRecordInfo( + message_number="52", + beginning_byte="38983378", + ending_byte="40192461", + initialization_date="d=2016010121", + variable="UGRD", + level="10 m above ground", + forecast="anl", + ) + assert g == expected + + +def test_grib_info_generate_grib_record_information_list(): + g_list = GribRecordInfo.generate_grib_record_information_list( + GRIB_RECORD_INFO_ARRAY, [0, 1] + ) + g = g_list[0] + expected = GribRecordInfo( + message_number="52", + beginning_byte="38983378", + ending_byte="40192461", + initialization_date="d=2016010121", + variable="UGRD", + level="10 m above ground", + forecast="anl", + ) + assert g == expected + + g = g_list[1] + expected = GribRecordInfo( + message_number="53", + beginning_byte="40192462", + ending_byte=None, + initialization_date="d=2016010121", + variable="VGRD", + level="10 m above ground", + forecast="anl", + ) + assert g == expected + + +def test_grib_info_byte_range_header_string(): + g = GribRecordInfo(None, "10", "20", None, None, None, None) + assert g.byte_range_header_string() == "10-20" + + +def test_grib_info_byte_range_header_string_no_end_byte(): + g = GribRecordInfo(None, "10", None, None, None, None, None) + assert g.byte_range_header_string() == "10-" diff --git a/prereise/gather/winddata/hrrr/tests/test_helpers.py b/prereise/gather/winddata/hrrr/tests/test_helpers.py new file mode 100644 index 000000000..c630661be --- /dev/null +++ b/prereise/gather/winddata/hrrr/tests/test_helpers.py @@ -0,0 +1,13 @@ +from prereise.gather.winddata.hrrr.helpers import get_indices_that_contain_selector + + +def test_get_indices_that_contain_selector(): + input_list = [ + "61:42783532:d=2016010100:CSNOW:surface:anl:", + "62:42816635:d=2016010100:CICEP:surface:anl:", + "63:42816823:d=2016010100:CFRZR:surface:anl:", + "64:42817132:d=2016010100:CRAIN:surface:anl:", + "65:42853953:d=2016010100:VGTYP:surface:anl:", + ] + selectors = ["CRAIN", "CSNOW"] + assert get_indices_that_contain_selector(input_list, selectors) == [0, 3] diff --git a/prereise/gather/winddata/hrrr/tests/test_hrrr_api.py b/prereise/gather/winddata/hrrr/tests/test_hrrr_api.py new file mode 100644 index 000000000..4ce177270 --- /dev/null +++ b/prereise/gather/winddata/hrrr/tests/test_hrrr_api.py @@ -0,0 +1,94 @@ +from unittest.mock import MagicMock, mock_open, patch + +import pytest + +from prereise.gather.winddata.hrrr.hrrr_api import HrrrApi + +CSNOW_SELECTOR = "CSNOW:surface" +CICEP_SELECTOR = "CICEP:surface" +UGRD_SELECTOR = "UGRD:80 m above ground" +VGRD_SELECTOR = "VGRD:80 m above ground" + +UGRD_BYTE_START = "43816635" +VGRD_BYTE_START = "44816635" +CICEP_BYTE_START = "42816635" +CSNOW_BYTE_START = "42783532" + +DIRECTORY = "./" +FILENAME = "somefile" +URL = "someurl" +FLAGS = "ab" + + +def filename_url_iter_mock(filename, url): + def _filename_url_iter(start_dt, end_dt, product): + yield filename, url + + return _filename_url_iter + + +@pytest.fixture +def requests_mock(): + with patch("prereise.gather.winddata.hrrr.hrrr_api.requests") as r: + r.get.return_value.text = ( + f"60:{CSNOW_BYTE_START}:d=2016010100:{CSNOW_SELECTOR}:anl:\n" + f"61:{CICEP_BYTE_START}:d=2016010100:{CICEP_SELECTOR}:anl:\n" + f"62:{UGRD_BYTE_START}:d=2016010100:{UGRD_SELECTOR}:anl:\n" + f"63:{VGRD_BYTE_START}:d=2016010100:{VGRD_SELECTOR}:anl:" + ) + yield r + + +@pytest.fixture +def open_mock(): + m = mock_open() + with patch("builtins.open", m): + yield m + + +@pytest.fixture +def hrrr_api(requests_mock, open_mock): + h = HrrrApi(MagicMock(), "") + h._filename_url_iter = filename_url_iter_mock(FILENAME, URL) + return h + + +def test_download_wind_data(open_mock, hrrr_api): + hrrr_api.download_wind_data(None, None, DIRECTORY) + + open_mock.assert_called_once_with(DIRECTORY + FILENAME, FLAGS) + hrrr_api.downloader.download.assert_any_call( + URL, + open_mock(), + headers={"Range": f"bytes={UGRD_BYTE_START}-{int(VGRD_BYTE_START)-1}"}, + ) + hrrr_api.downloader.download.assert_any_call( + URL, open_mock(), headers={"Range": f"bytes={VGRD_BYTE_START}-"} + ) + + +def test_download_meteorological_data_no_selectors(open_mock, hrrr_api): + hrrr_api.download_meteorological_data(None, None, DIRECTORY, None) + + open_mock.assert_called_once_with(DIRECTORY + FILENAME, FLAGS) + hrrr_api.downloader.download.assert_any_call( + URL, open_mock(), headers={"Range": "bytes=0-"} + ) + + +def test_download_meteorological_data_with_selectors(open_mock, hrrr_api): + hrrr_api.download_meteorological_data( + None, None, DIRECTORY, None, selectors=[CICEP_SELECTOR, CSNOW_SELECTOR] + ) + + open_mock.assert_called_once_with(DIRECTORY + FILENAME, FLAGS) + hrrr_api.downloader.download.assert_any_call( + URL, + open_mock(), + headers={"Range": f"bytes={CSNOW_BYTE_START}-{int(CICEP_BYTE_START)-1}"}, + ) + hrrr_api.downloader.download.assert_any_call( + URL, + open_mock(), + headers={"Range": f"bytes={CICEP_BYTE_START}-{int(UGRD_BYTE_START)-1}"}, + ) From 0ebbf2ded3cc89820481dffc1fab301bffa691bb Mon Sep 17 00:00:00 2001 From: George Tong Date: Mon, 13 Sep 2021 21:58:52 -0700 Subject: [PATCH 47/61] feat: calculate pout based on hrrr data --- Pipfile | 1 + docs/index.rst | 3 + docs/renewables/wind/hrrr.rst | 12 ++ prereise/gather/winddata/hrrr/calculations.py | 131 ++++++++++++++++++ prereise/gather/winddata/hrrr/constants.py | 3 + .../gather/winddata/hrrr/demo/hrrr_demo.ipynb | 61 ++++++++ prereise/gather/winddata/hrrr/helpers.py | 10 +- prereise/gather/winddata/hrrr/hrrr_api.py | 8 +- .../winddata/hrrr/tests/test_calculations.py | 70 ++++++++++ prereise/gather/winddata/rap/power_curves.py | 2 +- 10 files changed, 296 insertions(+), 5 deletions(-) create mode 100644 docs/renewables/wind/hrrr.rst create mode 100644 prereise/gather/winddata/hrrr/calculations.py create mode 100644 prereise/gather/winddata/hrrr/demo/hrrr_demo.ipynb create mode 100644 prereise/gather/winddata/hrrr/tests/test_calculations.py diff --git a/Pipfile b/Pipfile index 6d1df5161..07a9d57e4 100644 --- a/Pipfile +++ b/Pipfile @@ -24,3 +24,4 @@ netCDF4 = "==1.5.4" powersimdata = "~=0.4.4" nrel-pysam = "~=2.2" pyproj = "==2.6.1.post1" +pygrib = "*" diff --git a/docs/index.rst b/docs/index.rst index 7bfc7a778..28c8ee21e 100644 --- a/docs/index.rst +++ b/docs/index.rst @@ -83,6 +83,9 @@ Wind .. include:: renewables/wind/rap.rst +.. include:: + renewables/wind/hrrr.rst + .. include:: renewables/wind/method.rst diff --git a/docs/renewables/wind/hrrr.rst b/docs/renewables/wind/hrrr.rst new file mode 100644 index 000000000..a2a600fe2 --- /dev/null +++ b/docs/renewables/wind/hrrr.rst @@ -0,0 +1,12 @@ +High-Resolution Rapid Refresh +############# +The `HRRR`_ (High-Resolution Rapid Refresh) is a NOAA real-time 3-km resolution, +hourly updated, cloud-resolving, convection-allowing atmospheric model, initialized by +3km grids with 3km radar assimilation. Radar data is assimilated in the HRRR every 15 min +over a 1-h period adding further detail to that provided by the hourly data assimilation +from the 13km radar-enhanced Rapid Refresh. Data can be retrieved from a publicly available +AWS S3 `Bucket`_. + + +.. _HRRR: https://rapidrefresh.noaa.gov/hrrr/ +.. _Bucket: https://noaa-hrrr-bdp-pds.s3.amazonaws.com/index.html diff --git a/prereise/gather/winddata/hrrr/calculations.py b/prereise/gather/winddata/hrrr/calculations.py new file mode 100644 index 000000000..988b108b0 --- /dev/null +++ b/prereise/gather/winddata/hrrr/calculations.py @@ -0,0 +1,131 @@ +import numpy as np +import pandas as pd +import pygrib +from powersimdata.network.usa_tamu.constants.zones import id2abv +from powersimdata.utility.distance import ll2uv +from scipy.spatial import KDTree +from tqdm import tqdm + +from prereise.gather.winddata.hrrr.helpers import formatted_filename +from prereise.gather.winddata.rap.power_curves import ( + get_power, + get_state_power_curves, + get_turbine_power_curves, +) + +U_COMPONENT_SELECTOR = "U component of wind" +V_COMPONENT_SELECTOR = "V component of wind" + + +def get_wind_data_lat_long(dt, directory): + """Returns the latitude and longitudes of the various + wind grid sectors. Function assumes that there's data + for the dt provided and the data lives in the directory. + + :param datetime.datetime dt: date and time of the grib data + :param str directory: directory where the data is located + :return: (*tuple*) -- A tuple of 2 same lengthed numpy arrays, first one being + latitude and second one being longitude. + """ + gribs = pygrib.open(directory + formatted_filename(dt)) + grib = next(gribs) + return grib.latlons() + + +def find_closest_wind_grids(wind_farms, wind_data_lat_long): + """Uses provided wind farm data and wind grid data to calculate + the closest wind grid to each wind farm. + + :param pandas.DataFrame wind_farms: plant data frame. + :param tuple wind_data_lat_long: A tuple of 2 same lengthed numpy arrays, first one being + latitude and second one being longitude. + :return: (*numpy.array*) -- a numpy array that holds in each index i + the index of the closest wind grid in wind_data_lat_long for wind_farms i + """ + grid_lats, grid_lons = ( + wind_data_lat_long[0].flatten(), + wind_data_lat_long[1].flatten(), + ) + assert len(grid_lats) == len(grid_lons) + grid_lat_lon_unit_vectors = [ll2uv(i, j) for i, j in zip(grid_lons, grid_lats)] + + tree = KDTree(grid_lat_lon_unit_vectors) + + wind_farm_lats = wind_farms.lat.values + wind_farm_lons = wind_farms.lon.values + + wind_farm_unit_vectors = [ + ll2uv(i, j) for i, j in zip(wind_farm_lons, wind_farm_lats) + ] + _, indices = tree.query(wind_farm_unit_vectors) + + return indices + + +def calculate_pout(wind_farms, start_dt, end_dt, directory): + """Calculate power output for wind farms based on hrrr data. + Function assumes that user has already called + :meth:`prereise.gather.winddata.hrrr.hrrr.retrieve_data` with the same + start_dt, end_dt, and directory. + + :param pandas.DataFrame wind_farms: plant data frame. + :param str start_dt: start date. + :param str end_dt: end date (inclusive). + :param str directory: directory where hrrr data is contained. + :return: (*pandas.Dataframe*) -- Pandas containing power out per wind farm + on a per hourly basis between start_dt and end_dt inclusive. Structure of + dataframe is: + wind_farm1 wind_farm2 + dt1 POUT POUT + dt2 POUT POUT + """ + + wind_farm_ids = wind_farms.index + turbine_types = [ + "Offshore" + if wind_farms.loc[i].type == "wind_offshore" + else id2abv[wind_farms.loc[i].zone_id] + for i in wind_farm_ids + ] + wind_farm_ct = len(wind_farms) + + turbine_power_curves = get_turbine_power_curves() + state_power_curves = get_state_power_curves() + wind_data_lat_long = get_wind_data_lat_long(start_dt, directory) + wind_farm_to_closest_wind_grid_indices = find_closest_wind_grids( + wind_farms, wind_data_lat_long + ) + dts = [ + dt for dt in pd.date_range(start=start_dt, end=end_dt, freq="H").to_pydatetime() + ] + data = np.empty((len(dts), len(wind_farm_to_closest_wind_grid_indices))) + for i, dt in tqdm(enumerate(dts)): + gribs = pygrib.open(formatted_filename(dt)) + u_component = gribs.select(name=U_COMPONENT_SELECTOR)[0].values.flatten() + v_component = gribs.select(name=V_COMPONENT_SELECTOR)[0].values.flatten() + wind_farm_specific_u_component = u_component[ + wind_farm_to_closest_wind_grid_indices + ] + wind_farm_specific_v_component = v_component[ + wind_farm_to_closest_wind_grid_indices + ] + wind_farm_specific_magnitude = np.sqrt( + pow(wind_farm_specific_u_component, 2) + + pow(wind_farm_specific_v_component, 2) + ) + power = np.array( + [ + get_power( + turbine_power_curves, + state_power_curves, + wind_farm_specific_magnitude[j], + turbine_types[j], + ) + for j in range(wind_farm_ct) + ] + ) + data[i] = power + + df = pd.DataFrame(data=data, index=dts, columns=wind_farms.index) + + return df diff --git a/prereise/gather/winddata/hrrr/constants.py b/prereise/gather/winddata/hrrr/constants.py index 3222e5160..7efb5b020 100644 --- a/prereise/gather/winddata/hrrr/constants.py +++ b/prereise/gather/winddata/hrrr/constants.py @@ -4,3 +4,6 @@ HRRR_GOOGLE_BASE_URL = "https://storage.googleapis.com/high-resolution-rapid-refresh/hrrr.{dt:%Y%m%d}/conus/hrrr.t{dt:%Y%m%d}z.wrf{product}f{hours_forecasted:02d}.grib2" HRRR_AZURE_BASE_URL = "https://noaahrrr.blob.core.windows.net/hrrr/hrrr.{dt:%Y%m%d}/conus/hrrr.t{dt:%H}z.wrf{product}f{hours_forecasted:02d}.grib2" HRRR_NOMADS_BASE_URL = "https://nomads.ncep.noaa.gov/pub/data/nccf/com/hrrr/prod/hrrr.{dt:%Y%m%d}/conus/hrrr.t{dt:%H}z.wrf{product}f{hours_forecasted:02d}.grib2" + +DEFAULT_PRODUCT = "sfc" +DEFAULT_HOURS_FORECASTED = "0" diff --git a/prereise/gather/winddata/hrrr/demo/hrrr_demo.ipynb b/prereise/gather/winddata/hrrr/demo/hrrr_demo.ipynb new file mode 100644 index 000000000..8a1605b05 --- /dev/null +++ b/prereise/gather/winddata/hrrr/demo/hrrr_demo.ipynb @@ -0,0 +1,61 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "source": [ + "# Wind Data From NOAA's High-Resolution Rapid Refresh\n", + "---\n", + "\n", + "**NOAA**: National Oceanic and Atmospheric Administration\n", + "\n", + "**HRRR**: High-Resolution Rapid Refresh\n", + "\n", + "See documentation for more detail." + ], + "metadata": {} + }, + { + "cell_type": "code", + "execution_count": 1, + "source": [ + "from datetime import datetime\n", + "from prereise.gather.winddata.hrrr.hrrr import retrieve_data\n", + "from prereise.gather.winddata.hrrr.calculations import calculate_pout\n", + "from powersimdata.input.grid import Grid\n", + "\n", + "start_dt = datetime.fromisoformat(\"2016-01-01\")\n", + "end_dt = datetime.fromisoformat(\"2016-01-02\")\n", + "directory = \"./\"\n", + "\n", + "grid = Grid([\"Texas\",\"Western\"])\n", + "wind_farms = grid.plant.groupby(\"type\").get_group(\"wind\")\n", + "retrieve_data(start_dt=start_dt, end_dt=end_dt, directory=directory)\n", + "df = calculate_pout(wind_farms=wind_farms, start_dt=start_dt, end_dt=end_dt, directory=directory)\n", + "print(df.head())" + ], + "outputs": [], + "metadata": {} + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.3" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} \ No newline at end of file diff --git a/prereise/gather/winddata/hrrr/helpers.py b/prereise/gather/winddata/hrrr/helpers.py index 20da796cc..cd8b6aaa5 100644 --- a/prereise/gather/winddata/hrrr/helpers.py +++ b/prereise/gather/winddata/hrrr/helpers.py @@ -1,4 +1,12 @@ -def formatted_filename(dt, product, hours_forecasted): +from prereise.gather.winddata.hrrr.constants import ( + DEFAULT_HOURS_FORECASTED, + DEFAULT_PRODUCT, +) + + +def formatted_filename( + dt, product=DEFAULT_PRODUCT, hours_forecasted=DEFAULT_HOURS_FORECASTED +): """Deterministically returns a grib filename :param datetime.datetime dt: datetime associated with diff --git a/prereise/gather/winddata/hrrr/hrrr_api.py b/prereise/gather/winddata/hrrr/hrrr_api.py index 2bad8c631..1f9e4efcc 100644 --- a/prereise/gather/winddata/hrrr/hrrr_api.py +++ b/prereise/gather/winddata/hrrr/hrrr_api.py @@ -1,6 +1,8 @@ import requests from pandas import date_range +from tqdm import tqdm +from prereise.gather.winddata.hrrr.constants import DEFAULT_PRODUCT from prereise.gather.winddata.hrrr.grib import GribRecordInfo from prereise.gather.winddata.hrrr.helpers import ( formatted_filename, @@ -42,7 +44,7 @@ def _filename_url_iter(self, start_dt, end_dt, product): """ for dt in date_range(start=start_dt, end=end_dt, freq="H").to_pydatetime(): url = self.base_url.format(dt=dt, product=product, hours_forecasted=0) - yield formatted_filename(dt, product, hours_forecasted=0), url + yield formatted_filename(dt, product), url def download_meteorological_data( self, start_dt, end_dt, directory, product, selectors=None @@ -63,7 +65,7 @@ def download_meteorological_data( :param list selectors: list of strings that can be used to narrow down the amount of data downloaded from a specific GRIB file. """ - for filename, url in self._filename_url_iter(start_dt, end_dt, product): + for filename, url in tqdm(self._filename_url_iter(start_dt, end_dt, product)): grib_record_information_list = [GribRecordInfo.full_file()] # first grab index file and figure out which bytes to download if selectors: @@ -110,6 +112,6 @@ def download_wind_data(self, start_dt, end_dt, directory): start_dt, end_dt, directory, - product="sfc", + product=DEFAULT_PRODUCT, selectors=[self.U_COMPONENT_FILTER, self.V_COMPONENT_FILTER], ) diff --git a/prereise/gather/winddata/hrrr/tests/test_calculations.py b/prereise/gather/winddata/hrrr/tests/test_calculations.py new file mode 100644 index 000000000..585ccc68b --- /dev/null +++ b/prereise/gather/winddata/hrrr/tests/test_calculations.py @@ -0,0 +1,70 @@ +from datetime import datetime +from unittest.mock import MagicMock, patch + +import numpy as np +import pandas as pd + +from prereise.gather.winddata.hrrr.calculations import ( + calculate_pout, + find_closest_wind_grids, +) + + +def test_find_closest_wind_grids(): + wind_farms = MagicMock() + wind_farms.__len__.return_value = 2 + wind_farms.lat.values = [20, 40] + wind_farms.lon.values = [20, 40] + wind_data_lat = MagicMock() + wind_data_long = MagicMock() + + wind_data_lat.flatten.return_value = [19, 30, 41] + wind_data_long.flatten.return_value = [19, 30, 41] + assert np.array_equal( + np.array([0, 2]), + find_closest_wind_grids(wind_farms, [wind_data_lat, wind_data_long]), + ) + + +@patch("prereise.gather.winddata.hrrr.calculations.get_power") +@patch("prereise.gather.winddata.hrrr.calculations.get_wind_data_lat_long") +@patch("prereise.gather.winddata.hrrr.calculations.find_closest_wind_grids") +@patch("prereise.gather.winddata.hrrr.calculations.pygrib") +def test_calculate_pout( + pygrib, find_closest_wind_grids, get_wind_data_lat_long, get_power +): + # we assume get_power is well tested and simply return the magnitude value passed in + # for straightforward testing + def get_power_mock( + turbine_power_curves, + state_power_curves, + wind_farm_specific_magnitude, + turbine_types, + ): + return wind_farm_specific_magnitude + + get_power.side_effect = get_power_mock + find_closest_wind_grids.return_value = np.array([1, 2]) + + grib_mock = MagicMock() + + grib_mock.select.return_value.__getitem__.return_value.values.flatten.return_value = np.array( + [0, 1, 2] + ) + pygrib.open.return_value = grib_mock + wind_farms = MagicMock() + wind_farms.index = [0, 1] + wind_farms.loc.__getitem__.return_value.type = "wind_offshore" + wind_farms.__len__.return_value = 2 + df = calculate_pout( + wind_farms, + datetime.fromisoformat("2016-01-01"), + datetime.fromisoformat("2016-01-01"), + "", + ) + expected_df = pd.DataFrame( + data=[[np.sqrt(2), np.sqrt(8)]], + index=[datetime.fromisoformat("2016-01-01")], + columns=[0, 1], + ) + assert df.equals(expected_df) diff --git a/prereise/gather/winddata/rap/power_curves.py b/prereise/gather/winddata/rap/power_curves.py index 211a7fdeb..7333ad279 100644 --- a/prereise/gather/winddata/rap/power_curves.py +++ b/prereise/gather/winddata/rap/power_curves.py @@ -145,8 +145,8 @@ def get_power(power_curves, state_power_curves, wspd, turbine, default="IEC clas :param pandas.DataFrame power_curves: turbine power curves data. :param pandas.DataFrame state_power_curves: state average power curves data. :param float wspd: wind speed (in m/s). - :param str default: default turbine name. :param str turbine: turbine name, IEC class, or state code for average. + :param str default: default turbine name. :return: (*float*) -- normalized power. """ if turbine in state_power_curves.columns: From 5c856cdff417eb2dc2eccfeff82942888c777f3e Mon Sep 17 00:00:00 2001 From: jon-hagg <66005238+jon-hagg@users.noreply.github.com> Date: Mon, 20 Sep 2021 12:41:36 -0700 Subject: [PATCH 48/61] chore: update lockfile with pygrib (#1) --- Pipfile.lock | 133 +++++++++++++++++++++++++++++++++++---------------- 1 file changed, 91 insertions(+), 42 deletions(-) diff --git a/Pipfile.lock b/Pipfile.lock index f70ad59b3..c30242869 100644 --- a/Pipfile.lock +++ b/Pipfile.lock @@ -1,7 +1,7 @@ { "_meta": { "hash": { - "sha256": "c6bf0147eb1cbbe885779e8d4d1fbdecd1c7d64dcc681c677aea54622a77e830" + "sha256": "594b83774139995198f5f32bf0e99f54fa07fa3d44cb85005f2af9304592e554" }, "pipfile-spec": 6, "requires": {}, @@ -149,11 +149,11 @@ }, "charset-normalizer": { "hashes": [ - "sha256:0c8911edd15d19223366a194a513099a302055a962bca2cec0f54b8b63175d8b", - "sha256:f23667ebe1084be45f6ae0538e4a5a865206544097e4e8bbcacf42cd02a348f3" + "sha256:5d209c0a931f215cee683b6445e2d77677e7e75e159f78def0db09d68fafcaa6", + "sha256:5ec46d183433dcbd0ab716f2d7f29d8dee50505b3fdb40c6b985c7c4f5a3591f" ], "markers": "python_version >= '3'", - "version": "==2.0.4" + "version": "==2.0.6" }, "cryptography": { "hashes": [ @@ -164,6 +164,7 @@ "sha256:3520667fda779eb788ea00080124875be18f2d8f0848ec00733c0ec3bb8219fc", "sha256:3fa3a7ccf96e826affdf1a0a9432be74dc73423125c8f96a909e3835a5ef194a", "sha256:5b0fbfae7ff7febdb74b574055c7466da334a5371f253732d7e2e7525d570498", + "sha256:695104a9223a7239d155d7627ad912953b540929ef97ae0c34c7b8bf30857e89", "sha256:8695456444f277af73a4877db9fc979849cd3ee74c198d04fc0776ebc3db52b9", "sha256:94cc5ed4ceaefcbe5bf38c8fba6a21fc1d365bb8fb826ea1688e3370b2e24a1c", "sha256:94fff993ee9bc1b2440d3b7243d488c6a3d9724cc2b09cdb297f6a886d040ef7", @@ -187,11 +188,11 @@ }, "fonttools": { "hashes": [ - "sha256:47ce4aedc815a9d101d3b522c580264ca7e4a921cca6183ed460ad2c65d46f98", - "sha256:c1c0e03dd823e9e905232e875ea02dbb2dcd2ba195418c6d11bfaea49b9c774d" + "sha256:22ca101453fbc41fc5e34749402e41bdc41064b66daea80440cc12f501a45ad7", + "sha256:f12224bde50eaee537120fab09c3ad6f955059f530dfd24f70aa5228be327d72" ], "markers": "python_version >= '3.6'", - "version": "==4.26.2" + "version": "==4.27.0" }, "fs": { "hashes": [ @@ -218,11 +219,11 @@ }, "google-api-python-client": { "hashes": [ - "sha256:1f2657d1be246bc3d4bd1f0642f498653ce5fba507e6a05bbc405ed65bf10377", - "sha256:c89b345615188fbd525f52d59013156ad3bfd1023af27041f2dec3d7877ba112" + "sha256:0c8e81bec3a5f7c8bff8b8680f1a45c2ab34dcb445809dd5b1f8226dc56cc9c4", + "sha256:3b41c1a6b82792eb01e8a4bef3efb76b5c74151e866f7873d3de8ac2e5605bb4" ], "markers": "python_version >= '3.6'", - "version": "==2.19.1" + "version": "==2.21.0" }, "google-auth": { "hashes": [ @@ -473,11 +474,11 @@ }, "networkx": { "hashes": [ - "sha256:2306f1950ce772c5a59a57f5486d59bb9cab98497c45fc49cbc45ac0dec119bb", - "sha256:5fcb7004be69e8fbdf07dcb502efa5c77cadcaad6982164134eeb9721f826c2e" + "sha256:80b6b89c77d1dfb64a4c7854981b60aeea6360ac02c6d4e4913319e0a313abef", + "sha256:c0946ed31d71f1b732b5aaa6da5a0388a345019af232ce2f49c766e2d6795c51" ], "markers": "python_version >= '3.7'", - "version": "==2.6.2" + "version": "==2.6.3" }, "nrel-pysam": { "hashes": [ @@ -598,10 +599,12 @@ "sha256:04835e68ef12904bc3e1fd002b33eea0779320d4346082bd5b24bec12ad9c3e9", "sha256:06d1adaa284696785375fa80a6a8eb309be722cf4ef8949518beb34487a3df71", "sha256:085a90a99404b859a4b6c3daa42afde17cb3ad3115e44a75f0d7b4a32f06a6c9", + "sha256:0b9911ec70731711c3b6ebcde26caea620cbdd9dcb73c67b0730c8817f24711b", "sha256:10e00f7336780ca7d3653cf3ac26f068fa11b5a96894ea29a64d3dc4b810d630", "sha256:11c27e74bab423eb3c9232d97553111cc0be81b74b47165f07ebfdd29d825875", "sha256:11eb7f98165d56042545c9e6db3ce394ed8b45089a67124298f0473b29cb60b2", "sha256:13654b521fb98abdecec105ea3fb5ba863d1548c9b58831dd5105bb3873569f1", + 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python_version not in '3.0, 3.1, 3.2'", "version": "==1.16.0" }, + "tomli": { + "hashes": [ + "sha256:8dd0e9524d6f386271a36b41dbf6c57d8e32fd96fd22b6584679dc569d20899f", + "sha256:a5b75cb6f3968abb47af1b40c1819dc519ea82bcc065776a866e8d74c5ca9442" + ], + "markers": "python_version >= '3.6'", + "version": "==1.2.1" + }, "tornado": { "hashes": [ "sha256:0a00ff4561e2929a2c37ce706cb8233b7907e0cdc22eab98888aca5dd3775feb", @@ -1007,11 +1056,11 @@ }, "black": { "hashes": [ - "sha256:2a0f9a8c2b2a60dbcf1ccb058842fb22bdbbcb2f32c6cc02d9578f90b92ce8b7", - "sha256:570608d28aa3af1792b98c4a337dbac6367877b47b12b88ab42095cfc1a627c2" + "sha256:380f1b5da05e5a1429225676655dddb96f5ae8c75bdf91e53d798871b902a115", + "sha256:7de4cfc7eb6b710de325712d40125689101d21d25283eed7e9998722cf10eb91" ], "index": "pypi", - "version": "==21.8b0" + "version": "==21.9b0" }, "click": { "hashes": [ From 6c51efee31b66633116eda89e8870e7b9d4ec955 Mon Sep 17 00:00:00 2001 From: Ben RdO Date: Thu, 7 Oct 2021 13:43:12 -0700 Subject: [PATCH 49/61] docs: improve section on documentation in README (#231) --- README.md | 7 +++++-- 1 file changed, 5 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index 8b9a41b90..fb32f2940 100644 --- a/README.md +++ b/README.md @@ -57,7 +57,8 @@ third party dependencies. ## Documentation -The official documentation can be found [here][docs]. +[Code documentation][docstrings] in form of Python docstrings along with an overview of +the [package][docs] are available on our [website][website]. ## Communication Channels @@ -72,5 +73,7 @@ Guide](https://breakthrough-energy.github.io/docs/dev/contribution_guide.html). -[docs]: https://breakthrough-energy.github.io/docs/index.html +[docs]: https://breakthrough-energy.github.io/docs/prereise/index.html +[docstrings]: https://breakthrough-energy.github.io/docs/prereise.html +[website]: https://breakthrough-energy.github.io/docs/ [PowerSimData]: https://github.com/Breakthrough-Energy/PowerSimData From d19b98b91cfbf9060781ce81f34b49452f8b01bf Mon Sep 17 00:00:00 2001 From: Ben RdO Date: Tue, 12 Oct 2021 10:05:56 -0700 Subject: [PATCH 50/61] docs: change author (#232) --- setup.cfg | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/setup.cfg b/setup.cfg index 1726a0e7e..71944a7ff 100644 --- a/setup.cfg +++ b/setup.cfg @@ -1,8 +1,8 @@ [metadata] name = prereise version = 0.4 -author = Kaspar Mueller -author_email = kaspar@breakthroughenergy.org +author = Breakthrough Energy +author_email = sciences@breakthroughenergy.org description = Create and run an energy scenario long_description = file: README.md long_description_content_type = text/markdown From 6803270f1024fb2db8d0642060fb815120487757 Mon Sep 17 00:00:00 2001 From: Daniel Olsen Date: Mon, 6 Dec 2021 11:58:33 -0800 Subject: [PATCH 51/61] chore: move impute module one level up --- prereise/cli/data_sources/wind_data.py | 3 ++- prereise/gather/winddata/{rap => }/impute.py | 0 2 files changed, 2 insertions(+), 1 deletion(-) rename prereise/gather/winddata/{rap => }/impute.py (100%) diff --git a/prereise/cli/data_sources/wind_data.py b/prereise/cli/data_sources/wind_data.py index 87699772b..50771bbec 100644 --- a/prereise/cli/data_sources/wind_data.py +++ b/prereise/cli/data_sources/wind_data.py @@ -14,7 +14,8 @@ ) from prereise.cli.data_sources.data_source import DataSource from prereise.cli.helpers import validate_date, validate_file_path -from prereise.gather.winddata.rap import impute, rap +from prereise.gather.winddata import impute +from prereise.gather.winddata.rap import rap class WindDataRapidRefresh(DataSource): diff --git a/prereise/gather/winddata/rap/impute.py b/prereise/gather/winddata/impute.py similarity index 100% rename from prereise/gather/winddata/rap/impute.py rename to prereise/gather/winddata/impute.py From 889cffd5194fd6b53b7f798105af7994bc09ebc3 Mon Sep 17 00:00:00 2001 From: Daniel Olsen Date: Mon, 6 Dec 2021 12:44:04 -0800 Subject: [PATCH 52/61] feat: add linear imputation method --- prereise/gather/winddata/impute.py | 14 ++++++++++++++ 1 file changed, 14 insertions(+) diff --git a/prereise/gather/winddata/impute.py b/prereise/gather/winddata/impute.py index c46b447b5..d6b9b4506 100644 --- a/prereise/gather/winddata/impute.py +++ b/prereise/gather/winddata/impute.py @@ -137,3 +137,17 @@ def gaussian(data, wind_farm, inplace=True, curve="state"): if not inplace: return data_impute + + +def linear(data, inplace=True): + """Given a 2D array, linearly interpolate any missing values column-wise. + + :param numpy.array/pandas.DataFrame data: data to interpolate. + :param bool inplace: whether to modify the data inplace or return a modified copy. + :return: (*None/pandas.DataFrame*) -- if ``inplace`` is False, data frame with + missing entries imputed. + """ + data_impute = data if inplace else data.copy() + data_impute[:] = pd.DataFrame(data_impute).interpolate() + if not inplace: + return data_impute From 535b4d95a029a9b63bdfd932028c1954410531fa Mon Sep 17 00:00:00 2001 From: Daniel Olsen Date: Mon, 6 Dec 2021 11:11:29 -0800 Subject: [PATCH 53/61] fix: add try/except when querying from grib files, use linear imputation --- prereise/gather/winddata/hrrr/calculations.py | 79 ++++++++++--------- 1 file changed, 41 insertions(+), 38 deletions(-) diff --git a/prereise/gather/winddata/hrrr/calculations.py b/prereise/gather/winddata/hrrr/calculations.py index 988b108b0..fa91feaeb 100644 --- a/prereise/gather/winddata/hrrr/calculations.py +++ b/prereise/gather/winddata/hrrr/calculations.py @@ -7,6 +7,7 @@ from tqdm import tqdm from prereise.gather.winddata.hrrr.helpers import formatted_filename +from prereise.gather.winddata.impute import linear from prereise.gather.winddata.rap.power_curves import ( get_power, get_state_power_curves, @@ -80,14 +81,10 @@ def calculate_pout(wind_farms, start_dt, end_dt, directory): dt2 POUT POUT """ - wind_farm_ids = wind_farms.index - turbine_types = [ - "Offshore" - if wind_farms.loc[i].type == "wind_offshore" - else id2abv[wind_farms.loc[i].zone_id] - for i in wind_farm_ids - ] - wind_farm_ct = len(wind_farms) + turbine_types = wind_farms.apply( + lambda x: "Offshore" if x["type"] == "wind_offshore" else id2abv[x["zone_id"]], + axis=1, + ) turbine_power_curves = get_turbine_power_curves() state_power_curves = get_state_power_curves() @@ -95,37 +92,43 @@ def calculate_pout(wind_farms, start_dt, end_dt, directory): wind_farm_to_closest_wind_grid_indices = find_closest_wind_grids( wind_farms, wind_data_lat_long ) - dts = [ - dt for dt in pd.date_range(start=start_dt, end=end_dt, freq="H").to_pydatetime() - ] - data = np.empty((len(dts), len(wind_farm_to_closest_wind_grid_indices))) - for i, dt in tqdm(enumerate(dts)): + dts = pd.date_range(start=start_dt, end=end_dt, freq="H").to_pydatetime() + # Fetch wind speed data for each wind farm (or store NaN as applicable) + wind_speed_data = pd.DataFrame(index=dts, columns=wind_farms.index, dtype=float) + for dt in tqdm(dts): gribs = pygrib.open(formatted_filename(dt)) - u_component = gribs.select(name=U_COMPONENT_SELECTOR)[0].values.flatten() - v_component = gribs.select(name=V_COMPONENT_SELECTOR)[0].values.flatten() - wind_farm_specific_u_component = u_component[ - wind_farm_to_closest_wind_grid_indices - ] - wind_farm_specific_v_component = v_component[ - wind_farm_to_closest_wind_grid_indices - ] - wind_farm_specific_magnitude = np.sqrt( - pow(wind_farm_specific_u_component, 2) - + pow(wind_farm_specific_v_component, 2) - ) - power = np.array( - [ - get_power( - turbine_power_curves, - state_power_curves, - wind_farm_specific_magnitude[j], - turbine_types[j], - ) - for j in range(wind_farm_ct) + try: + u_component = gribs.select(name=U_COMPONENT_SELECTOR)[0].values.flatten() + v_component = gribs.select(name=V_COMPONENT_SELECTOR)[0].values.flatten() + wind_farm_specific_u_component = u_component[ + wind_farm_to_closest_wind_grid_indices ] - ) - data[i] = power - - df = pd.DataFrame(data=data, index=dts, columns=wind_farms.index) + wind_farm_specific_v_component = v_component[ + wind_farm_to_closest_wind_grid_indices + ] + wind_speed_data.loc[dt] = np.sqrt( + pow(wind_farm_specific_u_component, 2) + + pow(wind_farm_specific_v_component, 2) + ) + except ValueError: + # If the GRIB file is empty, no wind speed values can be selected + wind_speed_data.loc[dt] = np.nan + + # For each column, linearly interpolate any NaN values + linear(wind_speed_data) + # Then calculate wind power based on wind speed + wind_power_data = [ + [ + get_power( + turbine_power_curves, + state_power_curves, + wind_speed_data.loc[dt, w], + turbine_types.loc[w], + ) + for w in wind_farms.index + ] + for dt in tqdm(dts) + ] + df = pd.DataFrame(data=wind_power_data, index=dts, columns=wind_farms.index) return df From 5294e4335b73c89322622e58441a0f0cb47ae39e Mon Sep 17 00:00:00 2001 From: danielolsen Date: Fri, 17 Dec 2021 17:30:26 -0800 Subject: [PATCH 54/61] chore: disable tests for failing geo lookup API (#250) --- prereise/gather/demanddata/eia/tests/test_map_ba.py | 3 +++ 1 file changed, 3 insertions(+) diff --git a/prereise/gather/demanddata/eia/tests/test_map_ba.py b/prereise/gather/demanddata/eia/tests/test_map_ba.py index 0c6d76657..6a6a6f79d 100644 --- a/prereise/gather/demanddata/eia/tests/test_map_ba.py +++ b/prereise/gather/demanddata/eia/tests/test_map_ba.py @@ -1,4 +1,5 @@ import pandas as pd +import pytest from pandas.testing import assert_series_equal from prereise.gather.demanddata.eia.map_ba import ( @@ -67,6 +68,7 @@ def create_ba_to_region_dataframe(): return initial_df +@pytest.mark.skip(reason="Currently failing due to issues with the geo.fcc.gov API") def test_map_buses_to_county(): bus_df = pd.DataFrame( { @@ -81,6 +83,7 @@ def test_map_buses_to_county(): assert bus_no_county_match == [] +@pytest.mark.skip(reason="Currently failing due to issues with the geo.fcc.gov API") def test_map_buses_to_ba(): bus_df = pd.DataFrame( { From 57a59304553ae0774e885c59d505161a5ff0fcc2 Mon Sep 17 00:00:00 2001 From: Daniel Olsen Date: Wed, 1 Dec 2021 09:48:48 -0800 Subject: [PATCH 55/61] chore: add const.py file with state abbreviations --- prereise/gather/const.py | 53 ++++++++++++++++++++++++++++++++++++++++ 1 file changed, 53 insertions(+) create mode 100644 prereise/gather/const.py diff --git a/prereise/gather/const.py b/prereise/gather/const.py new file mode 100644 index 000000000..1ce78e33e --- /dev/null +++ b/prereise/gather/const.py @@ -0,0 +1,53 @@ +# Map state abbreviations to state name +abv2state = { + "AK": "Alaska", + "AL": "Alabama", + "AR": "Arkansas", + "AZ": "Arizona", + "CA": "California", + "CO": "Colorado", + "CT": "Connecticut", + "DE": "Delaware", + "FL": "Florida", + "GA": "Georgia", + "HI": "Hawaii", + "IA": "Iowa", + "ID": "Idaho", + "IL": "Illinois", + "IN": "Indiana", + "KS": "Kansas", + "KY": "Kentucky", + "LA": "Louisiana", + "MA": "Massachusetts", + "MD": "Maryland", + "ME": "Maine", + "MI": "Michigan", + "MN": "Minnesota", + "MO": "Missouri", + "MS": "Mississippi", + "MT": "Montana", + "NC": "North Carolina", + "ND": "North Dakota", + "NE": "Nebraska", + "NH": "New Hampshire", + "NJ": "New Jersey", + "NM": "New Mexico", + "NV": "Nevada", + "NY": "New York", + "OH": "Ohio", + "OK": "Oklahoma", + "OR": "Oregon", + "PA": "Pennsylvania", + "RI": "Rhode Island", + "SC": "South Carolina", + "SD": "South Dakota", + "TN": "Tennessee", + "TX": "Texas", + "UT": "Utah", + "VA": "Virginia", + "VT": "Vermont", + "WA": "Washington", + "WI": "Wisconsin", + "WV": "West Virginia", + "WY": "Wyoming", +} From 13129bddc77872e2c62b953a506dcb803f7fe253 Mon Sep 17 00:00:00 2001 From: Daniel Olsen Date: Wed, 1 Dec 2021 09:52:45 -0800 Subject: [PATCH 56/61] refactor: replace refs to PowerSimData state abbrevs with PreREISE --- prereise/gather/demanddata/nrel_efs/aggregate_demand.py | 3 ++- prereise/gather/demanddata/nrel_efs/get_efs_data.py | 3 ++- prereise/gather/helpers.py | 8 ++++---- prereise/gather/solardata/pv_tracking.py | 5 +++-- 4 files changed, 11 insertions(+), 8 deletions(-) diff --git a/prereise/gather/demanddata/nrel_efs/aggregate_demand.py b/prereise/gather/demanddata/nrel_efs/aggregate_demand.py index f8c089b8f..e292030a9 100644 --- a/prereise/gather/demanddata/nrel_efs/aggregate_demand.py +++ b/prereise/gather/demanddata/nrel_efs/aggregate_demand.py @@ -1,5 +1,6 @@ import pandas as pd -from powersimdata.network.usa_tamu.constants.zones import abv2state + +from prereise.gather.const import abv2state def combine_efs_demand(efs_dem=None, non_efs_dem=None, save=None): diff --git a/prereise/gather/demanddata/nrel_efs/get_efs_data.py b/prereise/gather/demanddata/nrel_efs/get_efs_data.py index df2f4d9df..a9d9dc450 100644 --- a/prereise/gather/demanddata/nrel_efs/get_efs_data.py +++ b/prereise/gather/demanddata/nrel_efs/get_efs_data.py @@ -6,7 +6,8 @@ import pandas as pd import requests -from powersimdata.network.usa_tamu.constants.zones import abv2state + +from prereise.gather.const import abv2state def download_demand_data( diff --git a/prereise/gather/helpers.py b/prereise/gather/helpers.py index 340cae46c..c6189e5d7 100644 --- a/prereise/gather/helpers.py +++ b/prereise/gather/helpers.py @@ -2,7 +2,8 @@ import numpy as np import pandas as pd -from powersimdata.network.usa_tamu.constants.zones import abv2loadzone + +from prereise.gather.const import abv2state def trim_eia_form_923(filename): @@ -46,10 +47,9 @@ def get_monthly_net_generation(state, eia_form_923, resource, hps=True): if not isinstance(resource, str): raise TypeError("resource must be a str") - if state not in abv2loadzone.keys(): + if state not in abv2state: raise ValueError( - "Invalid state. Possible states are %s" - % " | ".join(set(abv2loadzone.keys())) + "Invalid state. Possible states are %s" % " | ".join(set(abv2state)) ) all_resource = { diff --git a/prereise/gather/solardata/pv_tracking.py b/prereise/gather/solardata/pv_tracking.py index f25254ea2..3041f3b15 100644 --- a/prereise/gather/solardata/pv_tracking.py +++ b/prereise/gather/solardata/pv_tracking.py @@ -1,7 +1,8 @@ import os import pandas as pd -from powersimdata.network.usa_tamu.constants.zones import abv + +from prereise.gather.const import abv2state def get_pv_tracking_data(): @@ -46,7 +47,7 @@ def get_pv_tracking_ratio_state(pv_info, state): raise TypeError("state must be a list") for s in state: - if s not in abv: + if s not in abv2state.keys(): raise ValueError("Invalid State: %s" % s) pv_info_state = pv_info[pv_info["State"].isin(state)].copy() From 5a6524fc3303f0f0e0a4ea0df3cb6379d21dcfdb Mon Sep 17 00:00:00 2001 From: Daniel Olsen Date: Mon, 6 Dec 2021 19:44:25 -0800 Subject: [PATCH 57/61] refactor: make solar data retrieval flexible to grid model --- prereise/gather/solardata/nsrdb/sam.py | 39 +++++++++++++++++++------- 1 file changed, 29 insertions(+), 10 deletions(-) diff --git a/prereise/gather/solardata/nsrdb/sam.py b/prereise/gather/solardata/nsrdb/sam.py index 4646d6773..affc78270 100644 --- a/prereise/gather/solardata/nsrdb/sam.py +++ b/prereise/gather/solardata/nsrdb/sam.py @@ -2,11 +2,7 @@ import pandas as pd import PySAM.Pvwattsv7 as PVWatts import PySAM.PySSC as pssc # noqa: N813 -from powersimdata.network.usa_tamu.constants.zones import ( - abv2interconnect, - id2abv, - interconnect2abv, -) +from powersimdata.network.model import ModelImmutables from tqdm import tqdm from prereise.gather.solardata.helpers import get_plant_id_unique_location @@ -17,18 +13,40 @@ ) -def retrieve_data(solar_plant, email, api_key, year="2016", rate_limit=0.5): +def retrieve_data( + email, + api_key, + grid=None, + solar_plant=None, + grid_model=None, + year="2016", + rate_limit=0.5, +): """Retrieves irradiance data from NSRDB and calculate the power output using - the System Adviser Model (SAM). + the System Adviser Model (SAM). Either a Grid object needs to be passed to ``grid``, + or (a data frame needs to be passed to ``solar_plant`` and a string needs to be + passed to ``grid_model``. - :param pandas.DataFrame solar_plant: plant data frame. :param str email: email used to`sign up `_. :param str api_key: API key. + :param powersimdata.input.grid.Grid: grid instance. + :param pandas.DataFrame solar_plant: plant data frame. + :param str grid_model: string used to populate grid model lookup tables. :param str year: year. :param int/float rate_limit: minimum seconds to wait between requests to NREL :return: (*pandas.DataFrame*) -- data frame with *'Pout'*, *'plant_id'*, *'ts'* and *'ts_id'* as columns. Values are power output for a 1MW generator. """ + xor_err_msg = "Either grid xor (solar_plant and grid_model) must be defined" + if grid is None: + if solar_plant is None or grid_model is None: + raise TypeError(xor_err_msg) + mi = ModelImmutables(grid_model) + else: + if solar_plant is not None or grid_model is not None: + raise TypeError(xor_err_msg) + solar_plant = grid.plant.query("type == 'solar'").copy() + mi = grid.model_immutables # SAM only takes 365 days. try: @@ -53,11 +71,12 @@ def retrieve_data(solar_plant, email, api_key, year="2016", rate_limit=0.5): zone_id = solar_plant.zone_id.unique() frac = {} for i in zone_id: - state = id2abv[i] + state = mi.zones["id2abv"][i] frac[i] = get_pv_tracking_ratio_state(pv_info, [state]) if frac[i] is None: frac[i] = get_pv_tracking_ratio_state( - pv_info, list(interconnect2abv[abv2interconnect[state]]) + pv_info, + list(mi.zones["interconnect2abv"][mi.zones["abv2interconnect"][state]]), ) # Inverter Loading Ratio From 717b65bf5492769fd93f1241630796eb4b8a002f Mon Sep 17 00:00:00 2001 From: Daniel Olsen Date: Thu, 9 Dec 2021 15:25:21 -0800 Subject: [PATCH 58/61] refactor: make NREL query retry more resilient --- prereise/gather/solardata/nsrdb/nrel_api.py | 5 ++++- 1 file changed, 4 insertions(+), 1 deletion(-) diff --git a/prereise/gather/solardata/nsrdb/nrel_api.py b/prereise/gather/solardata/nsrdb/nrel_api.py index 2d95a6b23..afa27d30b 100644 --- a/prereise/gather/solardata/nsrdb/nrel_api.py +++ b/prereise/gather/solardata/nsrdb/nrel_api.py @@ -4,6 +4,7 @@ import pandas as pd import requests +from requests.exceptions import ConnectionError from prereise.gather.request_util import TransientError, retry @@ -131,7 +132,9 @@ def get_psm3_at(self, lat, lon, attributes, year, leap_day, dates=None): Psm3Data.check_attrs(attributes) url = self._build_url(lat, lon, attributes, year, leap_day) - @retry(interval=self.interval, allowed_exceptions=(TransientError)) + @retry( + interval=self.interval, allowed_exceptions=(TransientError, ConnectionError) + ) def download(url): resp = requests.get(url) if resp.status_code == 429: From 40f6ed15f03f467b9e5186d16faabadc4eee5453 Mon Sep 17 00:00:00 2001 From: Daniel Olsen Date: Mon, 13 Dec 2021 10:04:40 -0800 Subject: [PATCH 59/61] feat: add cache to NREL solar data download --- prereise/gather/solardata/nsrdb/nrel_api.py | 60 ++++++++++++++++----- 1 file changed, 46 insertions(+), 14 deletions(-) diff --git a/prereise/gather/solardata/nsrdb/nrel_api.py b/prereise/gather/solardata/nsrdb/nrel_api.py index afa27d30b..e17c22905 100644 --- a/prereise/gather/solardata/nsrdb/nrel_api.py +++ b/prereise/gather/solardata/nsrdb/nrel_api.py @@ -1,3 +1,5 @@ +import os +import pickle from dataclasses import dataclass from datetime import timedelta from io import BytesIO @@ -117,7 +119,20 @@ def _build_url(self, lat, lon, attributes, year="2016", leap_day=False): query = "&".join([f"{key}={value}" for key, value in payload.items()]) return f"{base_url}?{query}" - def get_psm3_at(self, lat, lon, attributes, year, leap_day, dates=None): + @staticmethod + def _build_filename(lat, lon, attributes, year="2016", leap_day=False): + parameters = { + "wkt": f"POINT({lon}%20{lat})", + "attributes": attributes, + "names": year, + "leap_day": str(leap_day).lower(), + } + filename = "&".join([f"{key}={value}" for key, value in parameters.items()]) + return f"{filename}.pkl" + + def get_psm3_at( + self, lat, lon, attributes, year, leap_day, dates=None, cache_dir=None + ): """Get PSM3 data at a given point for the specified year. :param str lat: latitude of the plant @@ -126,11 +141,10 @@ def get_psm3_at(self, lat, lon, attributes, year, leap_day, dates=None): :param str year: the year :param bool leap_day: whether to use a leap day :param pd.DatetimeIndex dates: if provided, use to index the downloaded data frame + :param str cache_dir: directory to cache downloaded data. If None, don't cache. :return: (*prereise.gather.solardata.nsrdb.nrel_api.Psm3Data*) -- a data class containing metadata and time series for the given year and location """ - Psm3Data.check_attrs(attributes) - url = self._build_url(lat, lon, attributes, year, leap_day) @retry( interval=self.interval, allowed_exceptions=(TransientError, ConnectionError) @@ -145,17 +159,35 @@ def download(url): raise Exception(f"Request failed: status_code={resp.status_code}") return resp - resp = download(url) - - info = pd.read_csv(BytesIO(resp.content), nrows=1) - data_resource = pd.read_csv(BytesIO(resp.content), dtype=float, skiprows=2) + def format_to_psm3data(resp): + info = pd.read_csv(BytesIO(resp.content), nrows=1) + data_resource = pd.read_csv(BytesIO(resp.content), dtype=float, skiprows=2) - tz, elevation = info["Local Time Zone"], info["Elevation"] + tz, elevation = info["Local Time Zone"], info["Elevation"] - if dates is not None: - data_resource.set_index( - dates + timedelta(hours=int(tz.values[0])), inplace=True + if dates is not None: + data_resource.set_index( + dates + timedelta(hours=int(tz.values[0])), inplace=True + ) + return Psm3Data( + float(lat), float(lon), float(tz), float(elevation), data_resource ) - return Psm3Data( - float(lat), float(lon), float(tz), float(elevation), data_resource - ) + + Psm3Data.check_attrs(attributes) + if cache_dir is not None: + os.makedirs(cache_dir, exist_ok=True) + filename = self._build_filename(lat, lon, attributes, year, leap_day) + filepath = os.path.join(cache_dir, filename) + try: + with open(filepath, "rb") as f: + psm3_data = pickle.load(f) + return psm3_data + except FileNotFoundError: + pass + url = self._build_url(lat, lon, attributes, year, leap_day) + resp = download(url) + psm3_data = format_to_psm3data(resp) + if cache_dir is not None: + with open(filepath, "wb") as f: + pickle.dump(psm3_data, f) + return psm3_data From d9210e3d225c00005b952b1ee0a0d2687a2b24de Mon Sep 17 00:00:00 2001 From: Daniel Olsen Date: Thu, 9 Dec 2021 09:19:20 -0800 Subject: [PATCH 60/61] refactor: rewrite sam.py with blended and individual plant modeling functions --- prereise/cli/data_sources/solar_data.py | 4 +- .../cli/data_sources/tests/test_solar_data.py | 18 +- prereise/gather/solardata/helpers.py | 1 - .../solardata/nsrdb/demo/nsrdb_sam_demo.ipynb | 1258 +++++++++++------ prereise/gather/solardata/nsrdb/sam.py | 273 ++-- 5 files changed, 1016 insertions(+), 538 deletions(-) diff --git a/prereise/cli/data_sources/solar_data.py b/prereise/cli/data_sources/solar_data.py index d3842905c..9ed1536fa 100644 --- a/prereise/cli/data_sources/solar_data.py +++ b/prereise/cli/data_sources/solar_data.py @@ -200,7 +200,9 @@ def extract( if method == NAIVE_STRING: data = naive.retrieve_data(solar_plants, email, key, year) elif method == SAM_STRING: - data = sam.retrieve_data(solar_plants, email, key, year) + data = sam.retrieve_data_blended( + email, key, solar_plants=solar_plants, year=year + ) else: raise ValueError(f"Unexpected method {method}") data.to_pickle(file_path) diff --git a/prereise/cli/data_sources/tests/test_solar_data.py b/prereise/cli/data_sources/tests/test_solar_data.py index 5b2a3a5eb..e13fc8d96 100644 --- a/prereise/cli/data_sources/tests/test_solar_data.py +++ b/prereise/cli/data_sources/tests/test_solar_data.py @@ -84,15 +84,15 @@ def test_solar_data_nsrdb_invalid_method(solar_data_nsrdb_object): def test_solar_data_nsrdb_happy_path(grid, solar_data_nsrdb_object): methods_to_test = [ - ("prereise.cli.data_sources.solar_data.sam", SAM_STRING), - ("prereise.cli.data_sources.solar_data.naive", NAIVE_STRING), + ("prereise.cli.data_sources.solar_data.sam.retrieve_data_blended", SAM_STRING), + ("prereise.cli.data_sources.solar_data.naive.retrieve_data", NAIVE_STRING), ] for patch_path, method_string in methods_to_test: with patch(patch_path) as method: solar_farms = MagicMock() data = MagicMock() - method.retrieve_data.return_value = data + method.return_value = data grid.return_value.plant.groupby.return_value.get_group.return_value = ( solar_farms ) @@ -105,7 +105,13 @@ def test_solar_data_nsrdb_happy_path(grid, solar_data_nsrdb_object): API_KEY, VALID_GRID_MODEL, ) - method.retrieve_data.assert_called_with( - solar_farms, EMAIL, API_KEY, STRING_YEAR_2020 - ) + if method_string == SAM_STRING: + method.assert_called_with( + EMAIL, API_KEY, solar_plants=solar_farms, year=STRING_YEAR_2020 + ) + elif method_string == NAIVE_STRING: + method.assert_called_with(solar_farms, EMAIL, API_KEY, STRING_YEAR_2020) + else: + raise Exception("Unknown method_string!") + data.to_pickle.assert_called_with(CURRENT_DIRECTORY_FILEPATH) diff --git a/prereise/gather/solardata/helpers.py b/prereise/gather/solardata/helpers.py index 1a3708ee8..059d7bb6f 100644 --- a/prereise/gather/solardata/helpers.py +++ b/prereise/gather/solardata/helpers.py @@ -6,7 +6,6 @@ def to_reise(data): :param pandas.DataFrame data: data frame as returned by :func:`prereise.gather.solardata.nsrdb.naive.retrieve_data`, - :func:`prereise.gather.solardata.nsrdb.sam.retrieve_data` or :func:`prereise.gather.solardata.ga_wind.ga_wind.retrieve_data` :return: (*pandas.DataFrame*) -- data frame formatted for REISE. :raises TypeError: if *'data'* is not a data frame. diff --git a/prereise/gather/solardata/nsrdb/demo/nsrdb_sam_demo.ipynb b/prereise/gather/solardata/nsrdb/demo/nsrdb_sam_demo.ipynb index b092fddc3..e224a3b55 100644 --- a/prereise/gather/solardata/nsrdb/demo/nsrdb_sam_demo.ipynb +++ b/prereise/gather/solardata/nsrdb/demo/nsrdb_sam_demo.ipynb @@ -154,7 +154,7 @@ " 12.00\n", " 1\n", " 10.0\n", - " 3.00\n", + " 0.0\n", " ...\n", " solar\n", " Texas\n", @@ -178,7 +178,7 @@ " 1.80\n", " 0\n", " 1.5\n", - " 0.45\n", + " 0.0\n", " ...\n", " solar\n", " Texas\n", @@ -202,7 +202,7 @@ " 276.00\n", " 0\n", " 230.0\n", - " 69.00\n", + " 0.0\n", " ...\n", " solar\n", " Texas\n", @@ -226,7 +226,7 @@ " 47.52\n", " 1\n", " 39.6\n", - " 11.88\n", + " 0.0\n", " ...\n", " solar\n", " Texas\n", @@ -250,7 +250,7 @@ " 1.68\n", " 1\n", " 1.4\n", - " 0.42\n", + " 0.0\n", " ...\n", " solar\n", " Texas\n", @@ -269,13 +269,13 @@ "" ], "text/plain": [ - " bus_id Pg Qg Qmax Qmin Vg mBase status Pmax Pmin \\\n", - "plant_id \n", - "12878 3001011 9.99 0.0 0.0 0.0 1.00 12.00 1 10.0 3.00 \n", - "12896 3001062 0.00 0.0 0.0 0.0 1.01 1.80 0 1.5 0.45 \n", - "12897 3001063 0.00 0.0 0.0 0.0 1.01 276.00 0 230.0 69.00 \n", - "12984 3003120 29.70 0.0 0.0 0.0 1.00 47.52 1 39.6 11.88 \n", - "13161 3006085 1.05 0.0 0.0 0.0 1.04 1.68 1 1.4 0.42 \n", + " bus_id Pg Qg Qmax Qmin Vg mBase status Pmax Pmin \\\n", + "plant_id \n", + "12878 3001011 9.99 0.0 0.0 0.0 1.00 12.00 1 10.0 0.0 \n", + "12896 3001062 0.00 0.0 0.0 0.0 1.01 1.80 0 1.5 0.0 \n", + "12897 3001063 0.00 0.0 0.0 0.0 1.01 276.00 0 230.0 0.0 \n", + "12984 3003120 29.70 0.0 0.0 0.0 1.00 47.52 1 39.6 0.0 \n", + "13161 3006085 1.05 0.0 0.0 0.0 1.04 1.68 1 1.4 0.0 \n", "\n", " ... type interconnect GenFuelCost GenIOB GenIOC GenIOD \\\n", "plant_id ... \n", @@ -314,12 +314,12 @@ "name": "stdout", "output_type": "stream", "text": [ - "There are 36 solar plants in the Eastern interconnection.\n" + "There are 36 solar plants in the Texas interconnection.\n" ] } ], "source": [ - "print(\"There are %d solar plants in the Eastern interconnection.\" % len(solar_plant))" + "print(\"There are %d solar plants in the Texas interconnection.\" % len(solar_plant))" ] }, { @@ -339,7 +339,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "email=brdo@intven.com\n", + "email=daniel@breakthroughenergy.org\n", "api_key=········\n" ] } @@ -358,12 +358,12 @@ "name": "stderr", "output_type": "stream", "text": [ - "100%|██████████| 17/17 [00:44<00:00, 2.42s/it]\n" + "100%|██████████████████████████████████████████| 17/17 [00:51<00:00, 3.14s/it]\n" ] } ], "source": [ - "data = sam.retrieve_data(solar_plant, email, key)" + "data = sam.retrieve_data_blended(email, key, grid=grid)" ] }, { @@ -392,179 +392,605 @@ " \n", " \n", " \n", - " Pout\n", - " plant_id\n", - " ts\n", - " ts_id\n", + " 12878\n", + " 12896\n", + " 12897\n", + " 12984\n", + " 13161\n", + " 13162\n", + " 13163\n", + " 13164\n", + " 13165\n", + " 13166\n", + " ...\n", + " 13997\n", + " 13998\n", + " 13999\n", + " 14000\n", + " 14001\n", + " 14002\n", + " 14003\n", + " 14004\n", + " 14005\n", + " 14006\n", " \n", " \n", " \n", " \n", - " 0\n", - " 0.0\n", - " 12878\n", - " 2016-01-01\n", - " 1\n", - " \n", - " \n", - " 1\n", - " 0.0\n", - " 12896\n", - " 2016-01-01\n", - " 1\n", - " \n", - " \n", - " 2\n", - " 0.0\n", - " 12897\n", - " 2016-01-01\n", - " 1\n", - " \n", - " \n", - " 3\n", - " 0.0\n", - " 12984\n", - " 2016-01-01\n", - " 1\n", - " \n", - " \n", - " 4\n", - " 0.0\n", - " 13161\n", - " 2016-01-01\n", - " 1\n", - " \n", - " \n", - " 5\n", - " 0.0\n", - " 13162\n", - " 2016-01-01\n", - " 1\n", + " 2016-01-01 00:00:00\n", + " 0.000000\n", + " 0.000000\n", + " 0.000000\n", + " 0.000000\n", + " 0.000000\n", + " 0.000000\n", + " 0.000000\n", + " 0.000000\n", + " 0.000000\n", + " 0.000000\n", + " ...\n", + " 0.000000\n", + " 0.000000\n", + " 0.000000\n", + " 0.000000\n", + " 0.000000\n", + " 0.000000\n", + " 0.000000\n", + " 0.000000\n", + " 0.000000\n", + " 0.000000\n", " \n", " \n", - " 6\n", - " 0.0\n", - " 13163\n", - " 2016-01-01\n", - " 1\n", + " 2016-01-01 01:00:00\n", + " 0.000000\n", + " 0.000000\n", + " 0.000000\n", + " 0.000000\n", + " 0.000000\n", + " 0.000000\n", + " 0.000000\n", + " 0.000000\n", + " 0.000000\n", + " 0.000000\n", + " ...\n", + " 0.000000\n", + " 0.000000\n", + " 0.000000\n", + " 0.000000\n", + " 0.000000\n", + " 0.000000\n", + " 0.000000\n", + " 0.000000\n", + " 0.000000\n", + " 0.000000\n", " \n", " \n", - 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20 rows × 36 columns

\n", "" ], "text/plain": [ - " Pout plant_id ts ts_id\n", - "0 0.0 12878 2016-01-01 1\n", - "1 0.0 12896 2016-01-01 1\n", - "2 0.0 12897 2016-01-01 1\n", - "3 0.0 12984 2016-01-01 1\n", - "4 0.0 13161 2016-01-01 1\n", - "5 0.0 13162 2016-01-01 1\n", - "6 0.0 13163 2016-01-01 1\n", - "7 0.0 13164 2016-01-01 1\n", - "8 0.0 13165 2016-01-01 1\n", - "9 0.0 13166 2016-01-01 1\n", - "10 0.0 13237 2016-01-01 1\n", - "11 0.0 13238 2016-01-01 1\n", - "12 0.0 13239 2016-01-01 1\n", - "13 0.0 13240 2016-01-01 1\n", - "14 0.0 13308 2016-01-01 1\n", - "15 0.0 13309 2016-01-01 1\n", - "16 0.0 13310 2016-01-01 1\n", - "17 0.0 13311 2016-01-01 1\n", - "18 0.0 13312 2016-01-01 1\n", - "19 0.0 13313 2016-01-01 1" + " 12878 12896 12897 12984 13161 \\\n", + "2016-01-01 00:00:00 0.000000 0.000000 0.000000 0.000000 0.000000 \n", + "2016-01-01 01:00:00 0.000000 0.000000 0.000000 0.000000 0.000000 \n", + "2016-01-01 02:00:00 0.000000 0.000000 0.000000 0.000000 0.000000 \n", + "2016-01-01 03:00:00 0.000000 0.000000 0.000000 0.000000 0.000000 \n", + "2016-01-01 04:00:00 0.000000 0.000000 0.000000 0.000000 0.000000 \n", + "2016-01-01 05:00:00 0.000000 0.000000 0.000000 0.000000 0.000000 \n", + "2016-01-01 06:00:00 0.000000 0.000000 0.000000 0.000000 0.000000 \n", + "2016-01-01 07:00:00 0.000000 0.000000 0.000000 0.000000 0.000000 \n", + "2016-01-01 08:00:00 0.000000 0.000000 0.000000 0.000000 0.000000 \n", + "2016-01-01 09:00:00 0.000000 0.000000 0.000000 0.000000 0.000000 \n", + "2016-01-01 10:00:00 0.000000 0.000000 0.000000 0.000000 0.000000 \n", + "2016-01-01 11:00:00 0.000000 0.000000 0.000000 0.000000 0.000000 \n", + "2016-01-01 12:00:00 0.000000 0.000000 0.000000 0.000000 0.000000 \n", + "2016-01-01 13:00:00 0.000000 0.000000 0.000000 0.000000 0.000000 \n", + "2016-01-01 14:00:00 0.000000 0.000000 0.000000 0.059885 0.042145 \n", + "2016-01-01 15:00:00 0.050717 0.054200 0.054200 0.113199 0.076352 \n", + "2016-01-01 16:00:00 0.110172 0.390702 0.390702 0.285293 0.399805 \n", + 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8 rows × 36 columns

\n", "" ], "text/plain": [ - " Pout plant_id ts_id\n", - "count 316224.000000 316224.000000 316224.000000\n", - "mean 0.287262 13506.527778 4392.500000\n", - "std 0.370628 410.426139 2535.726375\n", - "min 0.000000 12878.000000 1.000000\n", - "25% 0.000000 13165.750000 2196.750000\n", - "50% 0.000000 13311.500000 4392.500000\n", - "75% 0.671450 13997.250000 6588.250000\n", - "max 1.000000 14006.000000 8784.000000" + " 12878 12896 12897 12984 13161 \\\n", + "count 8784.000000 8784.000000 8784.000000 8784.000000 8784.000000 \n", + "mean 0.319473 0.305552 0.305552 0.280769 0.275564 \n", + "std 0.392525 0.384133 0.384133 0.365295 0.363075 \n", + "min 0.000000 0.000000 0.000000 0.000000 0.000000 \n", + "25% 0.000000 0.000000 0.000000 0.000000 0.000000 \n", + "50% 0.000000 0.000000 0.000000 0.000000 0.000000 \n", + "75% 0.770420 0.726192 0.726192 0.660864 0.628115 \n", + "max 1.000000 1.000000 1.000000 1.000000 1.000000 \n", + "\n", + " 13162 13163 13164 13165 13166 ... \\\n", + "count 8784.000000 8784.000000 8784.000000 8784.000000 8784.000000 ... \n", + "mean 0.275564 0.275564 0.275564 0.275564 0.275564 ... \n", + "std 0.363075 0.363075 0.363075 0.363075 0.363075 ... \n", + "min 0.000000 0.000000 0.000000 0.000000 0.000000 ... \n", + "25% 0.000000 0.000000 0.000000 0.000000 0.000000 ... \n", + "50% 0.000000 0.000000 0.000000 0.000000 0.000000 ... \n", + "75% 0.628115 0.628115 0.628115 0.628115 0.628115 ... \n", + "max 1.000000 1.000000 1.000000 1.000000 1.000000 ... \n", + "\n", + " 13997 13998 13999 14000 14001 \\\n", + "count 8784.000000 8784.000000 8784.000000 8784.000000 8784.000000 \n", + "mean 0.310299 0.302906 0.302906 0.313706 0.313175 \n", + "std 0.389951 0.385331 0.385331 0.391299 0.390747 \n", + "min 0.000000 0.000000 0.000000 0.000000 0.000000 \n", + "25% 0.000000 0.000000 0.000000 0.000000 0.000000 \n", + "50% 0.000000 0.000000 0.000000 0.000000 0.000000 \n", + "75% 0.748457 0.728051 0.728051 0.745061 0.763090 \n", + "max 1.000000 1.000000 1.000000 1.000000 1.000000 \n", + "\n", + " 14002 14003 14004 14005 14006 \n", + "count 8784.000000 8784.000000 8784.000000 8784.000000 8784.000000 \n", + "mean 0.315599 0.302906 0.317617 0.313706 0.297031 \n", + "std 0.393994 0.385331 0.395716 0.391299 0.379438 \n", + "min 0.000000 0.000000 0.000000 0.000000 0.000000 \n", + "25% 0.000000 0.000000 0.000000 0.000000 0.000000 \n", + "50% 0.000000 0.000000 0.000000 0.000000 0.000000 \n", + "75% 0.766505 0.728051 0.763064 0.745061 0.705764 \n", + "max 1.000000 1.000000 1.000000 1.000000 1.000000 \n", + "\n", + "[8 rows x 36 columns]" ] }, "execution_count": 8, @@ -713,8 +1334,7 @@ "metadata": {}, "outputs": [], "source": [ - "data_oneplant = data[data.plant_id == plant_id].set_index(\"ts\", drop=True).drop(\n", - " [\"plant_id\", \"ts_id\"], axis=1) * solar_plant.loc[plant_id, \"Pmax\"]" + "data_oneplant = data[plant_id] * solar_plant.loc[plant_id, \"Pmax\"]" ] }, { @@ -724,7 +1344,7 @@ "outputs": [ { "data": { - "image/png": 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\n", + "image/png": 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\n", 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" ] @@ -751,7 +1371,7 @@ "outputs": [ { "data": { - "image/png": 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\n", 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" ] @@ -785,274 +1405,20 @@ } ], "source": [ - "print(\"Capacity Factor: %.3f\" % (data_oneplant['Pout'].sum() / (366 * 24 * solar_plant.loc[plant_id].Pmax)))" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 4. Format Data\n", - "Data are formated for REISE" + "print(\"Capacity Factor: %.3f\" % (data_oneplant.sum() / (366 * 24 * solar_plant.loc[plant_id].Pmax)))" ] }, { "cell_type": "code", - "execution_count": 14, + "execution_count": null, "metadata": {}, "outputs": [], - "source": [ - "data_reise = to_reise(data)" - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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Either a Grid object needs to be passed to ``grid``, - or (a data frame needs to be passed to ``solar_plant`` and a string needs to be - passed to ``grid_model``. + or (a data frame needs to be passed to ``solar_plant`` and a dictionary needs to be + passed to ``interconnect_to_state_abvs``). :param str email: email used to`sign up `_. :param str api_key: API key. :param powersimdata.input.grid.Grid: grid instance. :param pandas.DataFrame solar_plant: plant data frame. - :param str grid_model: string used to populate grid model lookup tables. - :param str year: year. + :param dict/pandas.Series interconnect_to_state_abvs: mapping of interconnection + name to state abbreviations, used to look up average parameters by interconnect + when average parameters by state are not available. + :param int/str year: year. :param int/float rate_limit: minimum seconds to wait between requests to NREL + :param str cache_dir: directory to cache downloaded data. If None, don't cache. :return: (*pandas.DataFrame*) -- data frame with *'Pout'*, *'plant_id'*, *'ts'* and *'ts_id'* as columns. Values are power output for a 1MW generator. """ - xor_err_msg = "Either grid xor (solar_plant and grid_model) must be defined" + xor_err_msg = ( + "Either grid xor (solar_plant and interconnect_to_state_abvs) must be defined" + ) if grid is None: - if solar_plant is None or grid_model is None: + if solar_plant is None or interconnect_to_state_abvs is None: raise TypeError(xor_err_msg) - mi = ModelImmutables(grid_model) + if not {"state_abv", "interconnect"} <= set(solar_plant.columns): + raise ValueError("solar_plant needs 'state_abv' and 'interconnect' columns") + # Create mappings from other inputs + zone_id_to_state_abv = { + i: group["state_abv"].unique()[0] + for i, group in solar_plant.groupby("zone_id") + } + zone_id_to_interconnect = { + i: group["interconnect"].unique()[0] + for i, group in solar_plant.groupby("zone_id") + } else: - if solar_plant is not None or grid_model is not None: + if solar_plant is not None or interconnect_to_state_abvs is not None: raise TypeError(xor_err_msg) solar_plant = grid.plant.query("type == 'solar'").copy() - mi = grid.model_immutables - - # SAM only takes 365 days. - try: - leap_day = (pd.Timestamp("%s-02-29-00" % year).dayofyear - 1) * 24 - is_leap_year = True - dates = pd.date_range(start="%s-01-01-00" % 2015, freq="H", periods=365 * 24) - dates = dates.map(lambda t: t.replace(year=int(year))) - except ValueError: - leap_day = None - is_leap_year = False - dates = pd.date_range(start="%s-01-01-00" % year, freq="H", periods=365 * 24) - - # Identify unique location - coord = get_plant_id_unique_location(solar_plant) - - data = pd.DataFrame({"Pout": [], "plant_id": [], "ts": [], "ts_id": []}) + # Use existing mappings found in the Grid object + interconnect_to_state_abvs = grid.model_immutables.zones["interconnect2abv"] + zone_id_to_state_abv = grid.model_immutables.zones["id2abv"] + zone_id_to_interconnect = { + z: grid.model_immutables.zones["abv2interconnect"][zone_id_to_state_abv[z]] + for z in solar_plant["zone_id"].unique() + } + + real_dates = pd.date_range( + start=f"{year}-01-01-00", end=f"{year}-12-31-23", freq="H" + ) + sam_dates, leap_day = generate_timestamps_without_leap_day(year) # PV tracking ratios - # By state and by interconnect when EIA data do not have any solar PV in - # the state + # By state and by interconnect when EIA data do not have any solar PV in the state pv_info = get_pv_tracking_data() zone_id = solar_plant.zone_id.unique() frac = {} - for i in zone_id: - state = mi.zones["id2abv"][i] - frac[i] = get_pv_tracking_ratio_state(pv_info, [state]) - if frac[i] is None: - frac[i] = get_pv_tracking_ratio_state( - pv_info, - list(mi.zones["interconnect2abv"][mi.zones["abv2interconnect"][state]]), - ) + for zone in zone_id: + state = zone_id_to_state_abv[zone] + frac[zone] = get_pv_tracking_ratio_state(pv_info, [state]) + if frac[zone] is None: + interconnect = zone_id_to_interconnect[zone] + states_in_interconnect = list(interconnect_to_state_abvs[interconnect]) + frac[zone] = get_pv_tracking_ratio_state(pv_info, states_in_interconnect) # Inverter Loading Ratio ilr = 1.25 api = NrelApi(email, api_key, rate_limit) - for key in tqdm(coord.keys(), total=len(coord)): + # Identify unique location + coord = get_plant_id_unique_location(solar_plant) + + data = {} + for key, plants in tqdm(coord.items(), total=len(coord)): lat, lon = key[1], key[0] solar_data = api.get_psm3_at( lat, @@ -91,55 +146,105 @@ def retrieve_data( attributes="dhi,dni,wind_speed,air_temperature", year=year, leap_day=False, - dates=dates, + dates=sam_dates, + cache_dir=cache_dir, ).to_dict() - for i in coord[key]: - data_site = pd.DataFrame( - { - "ts": pd.date_range( - start="%s-01-01-00" % year, end="%s-12-31-23" % year, freq="H" - ) - } - ) - data_site["ts_id"] = range(1, len(data_site) + 1) - data_site["plant_id"] = i - - power = 0 - for j, axis in enumerate([0, 2, 4]): - pv_dict = { - "system_capacity": ilr, - "dc_ac_ratio": ilr, - "tilt": 30, - "azimuth": 180, - "inv_eff": 94, - "losses": 14, - "array_type": axis, - "gcr": 0.4, - "adjust:constant": 0, - } - - pv_dat = pssc.dict_to_ssc_table(pv_dict, "pvwattsv7") - pv = PVWatts.wrap(pv_dat) - pv.SolarResource.assign({"solar_resource_data": solar_data}) - pv.execute() - - ratio = frac[solar_plant.loc[i].zone_id][j] - power += ratio * np.array(pv.Outputs.gen) - - if is_leap_year is True: - data_site["Pout"] = np.insert( - power, leap_day, power[leap_day - 24 : leap_day] - ) + for i, plant_id in enumerate(plants): + if i == 0: + # Calculate power for the first plant at each location + first_plant_id = plant_id + tracking_ratios = frac[solar_plant.loc[plant_id].zone_id] + power = 0 + for j, axis in enumerate([0, 2, 4]): + plant_pv_dict = { + "system_capacity": ilr, + "dc_ac_ratio": ilr, + "array_type": axis, + } + pv_dict = {**default_pv_parameters, **plant_pv_dict} + power += tracking_ratios[j] * calculate_power(solar_data, pv_dict) + if leap_day is not None: + power = np.insert(power, leap_day, power[leap_day - 24 : leap_day]) else: - data_site["Pout"] = power + # For every other plant, look up power from first plant at the location + power = data[first_plant_id] + data[plant_id] = power - data = data.append(data_site, ignore_index=True, sort=False) + return pd.DataFrame(data, index=real_dates).sort_index(axis="columns") - data["plant_id"] = data["plant_id"].astype(np.int32) - data["ts_id"] = data["ts_id"].astype(np.int32) - data.sort_values(by=["ts_id", "plant_id"], inplace=True) - data.reset_index(inplace=True, drop=True) +def retrieve_data_individual( + email, api_key, solar_plant, year="2016", rate_limit=0.5, cache_dir=None +): + """Retrieves irradiance data from NSRDB and calculate the power output using + the System Adviser Model (SAM). Either a Grid object needs to be passed to ``grid``, + or (a data frame needs to be passed to ``solar_plant`` and a string needs to be + passed to ``grid_model``. + + :param str email: email used to`sign up `_. + :param str api_key: API key. + :param pandas.DataFrame solar_plant: plant data frame, plus additional boolean + columns 'Single-Axis Tracking?', 'Dual-Axis Tracking?', 'Fixed Tilt?', and float + columns 'Tilt Angle', 'Nameplate Capacity (MW)', and 'DC Net Capacity (MW)'. + :param int/str year: year. + :param int/float rate_limit: minimum seconds to wait between requests to NREL + :param str cache_dir: directory to cache downloaded data. If None, don't cache. + :return: (*pandas.DataFrame*) -- data frame with *'Pout'*, *'plant_id'*, + *'ts'* and *'ts_id'* as columns. Values are power output for a 1MW generator. + """ + # Verify that each solar plant has exactly one tracking type equal to True + array_type_mapping = { + "Fixed Tilt?": 0, + "Single-Axis Tracking?": 2, + "Dual-Axis Tracking?": 4, + } + if not all(solar_plant[array_type_mapping.keys()].sum(axis=1) == 1): + raise ValueError("Indeterminate tracking information for one or more plants") + # Select the appropriate 'array type' to pass to SAM + plant_array_types = ( + solar_plant[array_type_mapping.keys()] + .astype(bool) + .apply(lambda x: array_type_mapping[x.idxmax()], axis=1) + ) + + real_dates = pd.date_range( + start=f"{year}-01-01-00", end=f"{year}-12-31-23", freq="H" + ) + sam_dates, leap_day = generate_timestamps_without_leap_day(year) + + api = NrelApi(email, api_key, rate_limit) + + coord = get_plant_id_unique_location(solar_plant) + + data = {} + for key, plants in tqdm(coord.items(), total=len(coord)): + lat, lon = key[1], key[0] + solar_data = api.get_psm3_at( + lat, + lon, + attributes="dhi,dni,wind_speed,air_temperature", + year=year, + leap_day=False, + dates=sam_dates, + cache_dir=cache_dir, + ).to_dict() - return data + for plant_id in plants: + series = solar_plant.loc[plant_id] + ilr = series["DC Net Capacity (MW)"] / series["Nameplate Capacity (MW)"] + plant_pv_dict = { + "system_capacity": ilr, + "dc_ac_ratio": ilr, + "array_type": plant_array_types.loc[plant_id], + } + if plant_pv_dict["array_type"] == 0: + plant_pv_dict["tilt"] = series["Tilt Angle"] + pv_dict = {**default_pv_parameters, **plant_pv_dict} + power = calculate_power(solar_data, pv_dict) + if leap_day is not None: + power = np.insert(power, leap_day, power[leap_day - 24 : leap_day]) + + data[plant_id] = power + + return pd.DataFrame(data, index=real_dates).sort_index(axis="columns") From 98131ddfdd97d378a0378a70513e186b10327bc0 Mon Sep 17 00:00:00 2001 From: danielolsen Date: Tue, 4 Jan 2022 16:29:29 -0800 Subject: [PATCH 61/61] chore: narrow dependencies, bump version number to prepare for v0.4.1 release (#251) --- Pipfile | 4 ++-- requirements.txt | 4 ++-- setup.cfg | 2 +- 3 files changed, 5 insertions(+), 5 deletions(-) diff --git a/Pipfile b/Pipfile index 07a9d57e4..d404841a3 100644 --- a/Pipfile +++ b/Pipfile @@ -13,11 +13,11 @@ pytest-cov = "*" bokeh = "==2.0.2" h5pyd = "~=0.8" matplotlib = "~=3.3" -numpy = "~=1.20" +numpy = "~=1.21.0" pandas = "~=1.1.2" python-dateutil = "==2.7.5" requests = "~=2.25" -scipy = "~=1.6" +scipy = "~=1.7.0" tqdm = "==4.29.1" xlrd = "==1.2.0" netCDF4 = "==1.5.4" diff --git a/requirements.txt b/requirements.txt index 76b1ad139..1420c780e 100644 --- a/requirements.txt +++ b/requirements.txt @@ -2,13 +2,13 @@ bokeh==2.0.2 h5pyd~=0.8 matplotlib~=3.3 netCDF4==1.5.4 -numpy~=1.20 +numpy~=1.21.0 pandas~=1.1.2 powersimdata~=0.4.4 pyproj==2.6.1.post1 python-dateutil==2.7.5 requests~=2.25 -scipy~=1.6 +scipy~=1.7.0 tqdm==4.29.1 xlrd==1.2.0 nrel-pysam~=2.2 diff --git a/setup.cfg b/setup.cfg index 71944a7ff..426155f09 100644 --- a/setup.cfg +++ b/setup.cfg @@ -1,6 +1,6 @@ [metadata] name = prereise -version = 0.4 +version = 0.4.1 author = Breakthrough Energy author_email = sciences@breakthroughenergy.org description = Create and run an energy scenario