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Implement pvlib.irradiance.louche decomposition model #1705

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67 changes: 67 additions & 0 deletions pvlib/irradiance.py
Expand Up @@ -3117,3 +3117,70 @@
'dhi': dhi,
'dni': dni})
return component_sum_df


def pvl_louche(ghi, solar_zenith, datetime_or_doy):
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"""
Determine DNI and GHI from GHI using louche model.
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Parameters
----------
ghi : Series
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Global horizontal irradiance. [W/m^2]

zenith : Series
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True (not refraction-corrected) zenith angles in decimal
degrees. Angles must be >=0 and <=180.

datetime_or_doy : numeric, pandas.DatetimeIndex
Day of year or array of days of year e.g.
pd.DatetimeIndex.dayofyear, or pd.DatetimeIndex.

Returns
-------
data: OrderedDict or DataFrame
Contains the following keys/columns:

* ``dni``: the modeled direct normal irradiance in W/m^2.
* ``dhi``: the modeled diffuse horizontal irradiance in
W/m^2.
* ``kt``: Ratio of global to extraterrestrial irradiance
on a horizontal plane.

References
-------
.. [1] Louche A, Notton G, Poggi P, Simmonnot G. Correlations for direct
normal and global horizontal irradiation on French Mediterranean site.
Solar Energy
1991;46:261-6
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"""
bool = np.logical_or(solar_zenith > 180, solar_zenith < 0)
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solar_zenith = np.where(bool, np.NaN, solar_zenith)
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if np.isscalar(datetime_or_doy):
bool = (np.any(datetime_or_doy > 366 or datetime_or_doy < 1, axis=0))
print(bool)
datetime_or_doy = np.where(bool, np.NaN, datetime_or_doy)

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Added lines #L3162 - L3164 were not covered by tests
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# this is the I0 calculation from the reference
# SSC uses solar constant = 1366.1
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I0 = get_extra_radiation(datetime_or_doy)

I0h = I0*tools.cosd(solar_zenith)
Kt = ghi/I0h
pd.Series.clip(Kt, 0, inplace=True)
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kb = -10.627*Kt**5 + 15.307*Kt**4 - 5.205 * \
Kt**3 + 0.994*Kt**2 - 0.059*Kt + 0.002
dni = kb*I0
dhi = ghi-dni*tools.cosd(solar_zenith)
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data = OrderedDict()
data['dni'] = dni
data['dhi'] = dhi
data['kt'] = Kt

if isinstance(datetime_or_doy, pd.DatetimeIndex):
data = pd.DataFrame(data, index=datetime_or_doy)

return data
28 changes: 26 additions & 2 deletions pvlib/tests/test_irradiance.py
Expand Up @@ -246,6 +246,7 @@ def test_haydavies_components(irrad_data, ephem_data, dni_et):
assert_allclose(result['horizon'], expected['horizon'][-1], atol=1e-4)
assert isinstance(result, dict)


def test_reindl(irrad_data, ephem_data, dni_et):
result = irradiance.reindl(
40, 180, irrad_data['dhi'], irrad_data['dni'], irrad_data['ghi'],
Expand Down Expand Up @@ -903,8 +904,12 @@ def test_dirindex(times):
assert np.allclose(out, expected_out, rtol=tolerance, atol=0,
equal_nan=True)
tol_dirint = 0.2
assert np.allclose(out.values, dirint_close_values, rtol=tol_dirint, atol=0,
equal_nan=True)
assert np.allclose(
out.values,
dirint_close_values,
rtol=tol_dirint,
atol=0,
equal_nan=True)


def test_dirindex_min_cos_zenith_max_zenith():
Expand Down Expand Up @@ -1203,3 +1208,22 @@ def test_complete_irradiance():
dhi=None,
dni=i.dni,
dni_clear=clearsky.dni)


def test_pvl_louche():

index = pd.DatetimeIndex(['20190101']*3 + ['20190620']*3)
ghi = pd.Series([0, 50, 1000, 1000, 1000, 1000], index=index)
zenith = pd.Series([120, 85, 10, 10, 182, -2], index=index)
expected = pd.DataFrame(np.array(
[[2.827964, 1.413982, -0.000000],
[130.089669, 38.661938, 0.405724],
[828.498650, 184.088106, 0.718133],
[887.407348, 126.074364, 0.768214],
[np.NaN, np.NaN, np.NaN],
[np.NaN, np.NaN, np.NaN]]),
columns=['dni', 'dhi', 'kt'], index=index)

out = irradiance.pvl_louche(ghi, zenith, index)

assert assert_frame_equal(out, expected) is None
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