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fix modelchain with module temperature and arrays #1193

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Mar 12, 2021
Merged

fix modelchain with module temperature and arrays #1193

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1383179
fix modelchain with module temperature and arrays
wholmgren Mar 12, 2021
0c5bbd9
refactor to directly build from arrays
wholmgren Mar 12, 2021
fe95eff
add test
wholmgren Mar 12, 2021
708cefd
improve test
wholmgren Mar 12, 2021
0a4e2f2
fix test
wholmgren Mar 12, 2021
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8 changes: 6 additions & 2 deletions pvlib/modelchain.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1519,10 +1519,14 @@ def _prepare_temperature(self, data=None):
if not isinstance(data, tuple):
# broadcast data to all arrays
data = (data,) * self.system.num_arrays
# data is tuple, so temperature_model_parameters must also be
# tuple. system.temperature_model_parameters is reduced to a dict
# if system.num_arrays == 1, so manually access parameters. GH 1192
t_mod_params = tuple(array.temperature_model_parameters
for array in self.system.arrays)
# find where cell or module temperature is specified in input data
given_cell_temperature = tuple(itertools.starmap(
self._get_cell_temperature,
zip(data, poa, self.system.temperature_model_parameters)
self._get_cell_temperature, zip(data, poa, t_mod_params)
))
# If cell temperature has been specified for all arrays return
# immediately and do not try to compute it.
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32 changes: 32 additions & 0 deletions pvlib/tests/test_modelchain.py
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Original file line number Diff line number Diff line change
Expand Up @@ -830,6 +830,38 @@ def test__prepare_temperature(sapm_dc_snl_ac_system, location, weather,
assert_series_equal(mc.results.cell_temperature, data['cell_temperature'])


def test__prepare_temperature_len1_weather_tuple(
sapm_dc_snl_ac_system, location, weather, total_irrad):
# GH 1192
weather['module_temperature'] = [40., 30.]
data = weather.copy()

mc = ModelChain(sapm_dc_snl_ac_system, location, aoi_model='no_loss',
spectral_model='no_loss')
mc.run_model([data])
expected = pd.Series([42.617244212941394, 30.0], index=data.index)
assert_series_equal(mc.results.cell_temperature[0], expected)

data = weather.copy().rename(
columns={
"ghi": "poa_global", "dhi": "poa_diffuse", "dni": "poa_direct"}
)
mc = ModelChain(sapm_dc_snl_ac_system, location, aoi_model='no_loss',
spectral_model='no_loss')
mc.run_model_from_poa([data])
expected = pd.Series([41.5, 30.0], index=data.index)
assert_series_equal(mc.results.cell_temperature[0], expected)

data = weather.copy()[["module_temperature", "ghi"]].rename(
columns={"ghi": "effective_irradiance"}
)
mc = ModelChain(sapm_dc_snl_ac_system, location, aoi_model='no_loss',
spectral_model='no_loss')
mc.run_model_from_effective_irradiance([data])
expected = pd.Series([41.5, 30.0], index=data.index)
assert_series_equal(mc.results.cell_temperature[0], expected)


def test__prepare_temperature_arrays_weather(sapm_dc_snl_ac_system_same_arrays,
location, weather,
total_irrad):
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