def feedin_pvlib_test():
fn = os.path.join(os.path.dirname(__file__), os.pardir, 'tests', 'data',
'test_coastdat_weather.csv')
coastdat_id = '1126088'
weather = pd.read_csv(fn, header=[0, 1], index_col=[0],
parse_dates=True)[coastdat_id]
c = coastdat.fetch_data_coordinates_by_id(coastdat_id)
location = pvlib.location.Location(**getattr(c, '_asdict')())
pv_weather = coastdat.adapt_coastdat_weather_to_pvlib(weather, location)
sandia_modules = pvlib.pvsystem.retrieve_sam('sandiamod')
sapm_inverters = pvlib.pvsystem.retrieve_sam('sandiainverter')
pv = {
'pv_set_name': 'M_LG290G3__I_ABB_MICRO_025_US208',
'module_name': 'LG_LG290N1C_G3__2013_',
'module_key': 'LG290G3',
'inverter_name': 'ABB__MICRO_0_25_I_OUTD_US_208_208V__CEC_2014_',
'surface_azimuth': 180,
'surface_tilt': 35,
'albedo': 0.2
}
pv['module_parameters'] = sandia_modules[pv['module_name']]
pv['inverter_parameters'] = sapm_inverters[pv['inverter_name']]
pv['p_peak'] = pv['module_parameters'].Impo * pv['module_parameters'].Vmpo
eq_(int(feedin.feedin_pvlib(location, pv, pv_weather).sum()), 1025)
eq_(int(feedin.feedin_pvlib(location, pv, pv_weather).sum()), 1025)
def test_feedin_pv_sets():
fn = os.path.join(
os.path.dirname(__file__),
os.pardir,
"tests",
"data",
"test_coastdat_weather.csv",
)
pv_sets = feedin.create_pvlib_sets()
coastdat_id = "1126088"
weather = pd.read_csv(
fn,
header=[0, 1],
index_col=[0],
date_parser=lambda idx: pd.to_datetime(idx, utc=True),
)[coastdat_id]
c = coastdat.fetch_data_coordinates_by_id(coastdat_id)
location = pvlib.location.Location(**getattr(c, "_asdict")())
pv_weather = coastdat.adapt_coastdat_weather_to_pvlib(weather, location)
s1 = pd.Series()
for pv_key, pv_set in pv_sets.items():
s1[pv_key] = int((feedin.feedin_pv_sets(pv_weather, location,
pv_set).sum().mean()))
s2 = pd.Series({
"M_STP280S__I_GEPVb_5000_NA_240": 550,
"M_BP2150S__I_P235HV_240": 725,
"M_SF160S___I_ABB_MICRO_025_US208": 797,
"M_LG290G3__I_ABB_MICRO_025_US208": 815,
})
pd.testing.assert_series_equal(s1.sort_index(), s2.sort_index())
def feedin_pv_sets_tests():
fn = os.path.join(os.path.dirname(__file__), os.pardir, 'tests', 'data',
'test_coastdat_weather.csv')
pv_sets = feedin.create_pvlib_sets()
coastdat_id = '1126088'
weather = pd.read_csv(fn, header=[0, 1], index_col=[0],
parse_dates=True)[coastdat_id]
c = coastdat.fetch_data_coordinates_by_id(coastdat_id)
location = pvlib.location.Location(**getattr(c, '_asdict')())
pv_weather = coastdat.adapt_coastdat_weather_to_pvlib(weather, location)
s1 = pd.Series()
for pv_key, pv_set in pv_sets.items():
s1[pv_key] = int((feedin.feedin_pv_sets(pv_weather, location,
pv_set).sum().mean()))
s2 = pd.Series({
'M_STP280S__I_GEPVb_5000_NA_240': 798,
'M_BP2150S__I_P235HV_240': 722,
'M_SF160S___I_ABB_MICRO_025_US208': 801,
'M_LG290G3__I_ABB_MICRO_025_US208': 817
})
pd.testing.assert_series_equal(s1.sort_index(), s2.sort_index())
def test_feedin_pvlib():
fn = os.path.join(
os.path.dirname(__file__),
os.pardir,
"tests",
"data",
"test_coastdat_weather.csv",
)
coastdat_id = "1126088"
weather = pd.read_csv(
fn,
header=[0, 1],
index_col=[0],
date_parser=lambda idx: pd.to_datetime(idx, utc=True),
)[coastdat_id]
c = coastdat.fetch_data_coordinates_by_id(coastdat_id)
location = pvlib.location.Location(**getattr(c, "_asdict")())
pv_weather = coastdat.adapt_coastdat_weather_to_pvlib(weather, location)
sandia_modules = pvlib.pvsystem.retrieve_sam("sandiamod")
sapm_inverters = pvlib.pvsystem.retrieve_sam("sandiainverter")
pv = {}
for k, v in cfg.get_dict("solar_set3").items():
if isinstance(v, str):
pv[k] = v.split(",")[0]
else:
pv[k] = v
try:
pv[k] = float(pv[k])
except ValueError:
pass
pv["module_parameters"] = sandia_modules[pv["module_name"]]
pv["inverter_parameters"] = sapm_inverters[pv["inverter_name"]]
pv["p_peak"] = pv["module_parameters"].Impo * pv["module_parameters"].Vmpo
assert int(feedin.feedin_pvlib(location, pv, pv_weather).sum()) == 899
def feedin_pvlib_test():
fn = os.path.join(
os.path.dirname(__file__),
os.pardir,
"tests",
"data",
"test_coastdat_weather.csv",
)
coastdat_id = "1126088"
weather = pd.read_csv(
fn,
header=[0, 1],
index_col=[0],
date_parser=lambda idx: pd.to_datetime(idx, utc=True),
)[coastdat_id]
c = coastdat.fetch_data_coordinates_by_id(coastdat_id)
location = pvlib.location.Location(**getattr(c, "_asdict")())
pv_weather = coastdat.adapt_coastdat_weather_to_pvlib(weather, location)
sandia_modules = pvlib.pvsystem.retrieve_sam("sandiamod")
sapm_inverters = pvlib.pvsystem.retrieve_sam("sandiainverter")
pv = {
"pv_set_name": "M_LG290G3__I_ABB_MICRO_025_US208",
"module_name": "LG_LG290N1C_G3__2013_",
"module_key": "LG290G3",
"inverter_name": "ABB__MICRO_0_25_I_OUTD_US_208_208V__CEC_2014_",
"surface_azimuth": 180,
"surface_tilt": 35,
"albedo": 0.2,
}
pv["module_parameters"] = sandia_modules[pv["module_name"]]
pv["inverter_parameters"] = sapm_inverters[pv["inverter_name"]]
pv["p_peak"] = pv["module_parameters"].Impo * pv["module_parameters"].Vmpo
eq_(int(feedin.feedin_pvlib(location, pv, pv_weather).sum()), 1025)
eq_(int(feedin.feedin_pvlib(location, pv, pv_weather).sum()), 1025)