def test_run_fast_mode_segments(params):
"""Test that PV engine works for timeseries fast mode and float inputs.
Value is very close to loop-like fast mode"""
# Discretize middle PV row's back side
params.update({'cut': {1: {'back': 5}}})
# Prepare some engine inputs
irradiance_model = HybridPerezOrdered()
pvarray = OrderedPVArray.init_from_dict(
params, param_names=irradiance_model.params)
fast_mode_pvrow_index = 1
fast_mode_segment_index = 2
# Create engine object
eng = PVEngine(pvarray,
irradiance_model=irradiance_model,
fast_mode_pvrow_index=fast_mode_pvrow_index,
fast_mode_segment_index=fast_mode_segment_index)
# Irradiance inputs
timestamps = dt.datetime(2019, 6, 11, 11)
DNI = 1000.
DHI = 100.
# Fit engine
eng.fit(timestamps, DNI, DHI, params['solar_zenith'],
params['solar_azimuth'], params['surface_tilt'],
params['surface_azimuth'], params['rho_ground'])
# Checks
np.testing.assert_almost_equal(eng.irradiance.direct['front_illum_pvrow'],
DNI)
# Define report function to grab irradiance from PV row segment
def fn_report(pvarray):
return (pvarray.ts_pvrows[1].back.list_segments[2].get_param_weighted(
'qinc'))
# Expected value for middle segment
qinc_expected = 116.572594
# Run fast mode for specific segment
qinc_segment = eng.run_fast_mode(fn_build_report=fn_report)
# Check results
np.testing.assert_allclose(qinc_segment, qinc_expected)
# Without providing segment index: the value should be the same as above
eng.fast_mode_segment_index = None
qinc_segment = eng.run_fast_mode(fn_build_report=fn_report)
# Check results
np.testing.assert_allclose(qinc_segment, qinc_expected)
def test_run_fast_mode_back_shading(params):
"""Test that PV engine works for timeseries fast mode and float inputs,
and when there's large direct shading on the back surface.
Value is very close to loop-style fast mode"""
params.update({
'gcr': 0.6,
'surface_azimuth': 270,
'surface_tilt': 120,
'solar_zenith': 70.
})
# Prepare some engine inputs
irradiance_model = HybridPerezOrdered()
pvarray = OrderedPVArray.init_from_dict(
params, param_names=irradiance_model.params)
fast_mode_pvrow_index = 1
fast_mode_segment_index = 0
# Create engine object
eng = PVEngine(pvarray,
irradiance_model=irradiance_model,
fast_mode_pvrow_index=fast_mode_pvrow_index,
fast_mode_segment_index=fast_mode_segment_index)
# Irradiance inputs
timestamps = dt.datetime(2019, 6, 11, 11)
DNI = 1000.
DHI = 100.
# Expected values
expected_qinc = 683.537153
# Fit engine
eng.fit(timestamps, DNI, DHI, params['solar_zenith'],
params['solar_azimuth'], params['surface_tilt'],
params['surface_azimuth'], params['rho_ground'])
def fn_report(pvarray):
return (pvarray.ts_pvrows[1].back.get_param_weighted('qinc'))
# By providing segment index
qinc = eng.run_fast_mode(fn_build_report=fn_report)
# Check results
np.testing.assert_allclose(qinc, expected_qinc)
# Without providing segment index
eng.fast_mode_segment_index = None
qinc = eng.run_fast_mode(fn_build_report=fn_report)
# Check results
np.testing.assert_allclose(qinc, expected_qinc)
def test_run_fast_mode_isotropic(params):
"""Test that PV engine works for timeseries fast mode and float inputs,
and using the isotropic irradiance model"""
# Prepare some engine inputs
irradiance_model = IsotropicOrdered()
pvarray = OrderedPVArray.init_from_dict(
params, param_names=irradiance_model.params)
fast_mode_pvrow_index = 1
fast_mode_segment_index = 0
# Create engine object
eng = PVEngine(pvarray, irradiance_model=irradiance_model,
fast_mode_pvrow_index=fast_mode_pvrow_index,
fast_mode_segment_index=fast_mode_segment_index)
# Irradiance inputs
timestamps = dt.datetime(2019, 6, 11, 11)
DNI = 1000.
DHI = 100.
# Fit engine
eng.fit(timestamps, DNI, DHI,
params['solar_zenith'], params['solar_azimuth'],
params['surface_tilt'], params['surface_azimuth'],
params['rho_ground'])
# Checks
np.testing.assert_almost_equal(eng.irradiance.direct['front_illum_pvrow'],
DNI)
# Expected value
qinc_expected = 122.73453
# Run fast mode
qinc = eng.run_fast_mode(
fn_build_report=lambda pvarray: (pvarray.ts_pvrows[1]
.back.get_param_weighted('qinc')))
# Check results
np.testing.assert_allclose(qinc, qinc_expected)
# Without providing segment index
eng.fast_mode_segment_index = None
qinc = eng.run_fast_mode(
fn_build_report=lambda pvarray: (pvarray.ts_pvrows[1]
.back.get_param_weighted('qinc')))
# Check results
np.testing.assert_allclose(qinc, qinc_expected)