def test_normalization_with_pvw(self):
''' Test PVWatts normalization. '''
pvw_kws = {
'poa_global': self.poa_global,
'P_ref': self.power,
'T_cell': self.temp,
'gamma_pdc': self.gamma_pdc,
}
corr_energy, insolation = normalize_with_pvwatts(self.energy, pvw_kws)
# Test output is same frequency and length as energy
self.assertEqual(corr_energy.index.freq, self.energy.index.freq)
self.assertEqual(len(corr_energy), 12)
# Test corrected energy is equal to 1.0
self.assertTrue((corr_energy == 1.0).all())
# Test expected behavior when energy has no explicit frequency
self.energy.index.freq = None
corr_energy, insolation = normalize_with_pvwatts(self.energy, pvw_kws)
self.assertTrue(np.isnan(
corr_energy.iloc[0])) # first valye should be nan
self.assertTrue(
(corr_energy.iloc[1:] == 1.0).all()) # rest should be 1
# Test for valueError when energy frequency can't be inferred
with self.assertRaises(ValueError):
corr_energy, insolation = normalize_with_pvwatts(
self.irregular_timeseries, pvw_kws)
def test_normalization_with_pvw(self):
''' Test PVWatts normalization. '''
pvw_kws = {
'poa_global': self.poa_global,
'power_dc_rated': self.power,
'temperature_cell': self.temp,
'gamma_pdc': self.gamma_pdc,
}
with pytest.warns(rdtoolsDeprecationWarning):
corr_energy, insolation = normalize_with_pvwatts(
self.energy, pvw_kws)
corr_energy = corr_energy.reindex(self.energy.index)
# Test output is same frequency and length as energy
self.assertEqual(corr_energy.index.freq, self.energy.index.freq)
self.assertEqual(len(corr_energy), 12)
# Test corrected energy is equal to 1.0
# first value should be nan because we have no irradiance
# data prior to the first energy point
self.assertTrue(np.isnan(corr_energy.iloc[0]))
self.assertTrue(
(corr_energy.iloc[1:] == 1.0).all()) # rest should be 1
# Test expected behavior when energy has no explicit frequency
self.energy.index.freq = None
with pytest.warns(rdtoolsDeprecationWarning):
corr_energy, insolation = normalize_with_pvwatts(
self.energy, pvw_kws)
corr_energy = corr_energy.reindex(self.energy.index)
self.assertTrue(np.isnan(
corr_energy.iloc[0])) # first value should be nan
self.assertTrue(
(corr_energy.iloc[1:] == 1.0).all()) # rest should be 1
# Test for valueError when energy frequency can't be inferred
with self.assertRaises(ValueError):
with pytest.warns(rdtoolsDeprecationWarning):
corr_energy, insolation = normalize_with_pvwatts(
self.irregular_timeseries, pvw_kws)
def _pvwatts_norm(self, poa_global, temperature_cell):
'''
Normalize PV energy to that expected from a PVWatts model.
Parameters
---------
poa_global : numeric
plane of array irradiance in W/m^2
temperature_cell : numeric
cell temperature in Celsius
Returns
-------
pandas.Series
Normalized pv energy
pandas.Series
Associated insolation
'''
if self.power_dc_rated is None:
renorm = True
power_dc_rated = 1.0
else:
renorm = False
power_dc_rated = self.power_dc_rated
if self.gamma_pdc is None:
warnings.warn(
'Temperature coefficient not passed in to TrendAnalysis'
'. No temperature correction will be conducted.')
pvwatts_kws = {
"poa_global": poa_global,
"power_dc_rated": power_dc_rated,
"temperature_cell": temperature_cell,
"poa_global_ref": 1000,
"temperature_cell_ref": 25,
"gamma_pdc": self.gamma_pdc
}
energy_normalized, insolation = normalization.normalize_with_pvwatts(
self.pv_energy, pvwatts_kws)
if renorm:
# Normalize to the 95th percentile for convenience, this is renormalized out
# in the calculations but is relevant to normalized_filter()
x = energy_normalized[np.isfinite(energy_normalized)]
energy_normalized = energy_normalized / x.quantile(0.95)
return energy_normalized, insolation
def test_normalization_with_pvw(self):
''' Test PVWatts normalization. '''
pvw_kws = {
'poa_global': self.poa_global,
'P_ref': self.power,
'T_cell': self.temp,
'gamma_pdc': self.gamma_pdc,
}
corr_energy = normalize_with_pvwatts(self.energy, pvw_kws)
# Test output is same frequency and length as energy
self.assertEqual(corr_energy.index.freq, self.energy.index.freq)
self.assertEqual(len(corr_energy), 12)
# Test corrected energy is equal to 1.0
self.assertTrue((corr_energy == 1.0).all())