Add PVSPEC spectral correction factor model

pvlib/spectrum/__init__.py

@@ -6,4 +6,5 @@
  spectral_factor_caballero,
  spectral_factor_firstsolar,
  spectral_factor_sapm,
+ spectral_factor_pelland
 )

pvlib/spectrum/mismatch.py

@@ -571,3 +571,128 @@
  )
  modifier = f_AM + f_AOD + f_PW # Eq 5
  return modifier
+
+def spectral_factor_pelland(airmass_absolute, clearness_index,
+ module_type = None, coefficients = None,
+ min_airmass_absolute = 0.58,
+ max_airmass_absolute = 10):
+ r"""
+ Estimate a technology-specific spectral mismatch modifier from
+ airmass and clearness index using the Pelland model, which takes the
+ following form:
+
+ .. math::
+
+ M = a_1*kc**(a_2)*ama**(a_3),
+
+ where M is the spectral mismatch factor, and a_1, a_2, a_3 are
+ module-specific coefficients.
+
+ The motivtion for this model is to include the effect of cloud cover on the
+ spectrum, and thus spectral mismatch. Another motivation is to develop a
+ simple parameterisation compared with existing models. Model coefficients
+ are derived using spectral irradiance and other meteorological data from
+ eight locations. These coefficients for seven modules, available here via
+ the ``module_type`` parameter, as well as more details on the model, can be
+ found in Ref. [1]_
+
+ Parameters
+ ----------
+ airmass_absolute : numeric
+ absolute (pressure-adjusted) airmass. [unitless]
+
+ clearness_index: numeric
+ clearness index. [unitless]
+
+ module_type : str, optional
+ One of the following PV technology strings from [1]_:
+
+ * ``'fs4-1'`` - First Solar series 4-1 and earlier CdTe module.
+ * ``'fs4-2'`` - First Solar 4-2 and earlier CdTe module.
+ * ``'monosi'``, - anonymous sc-si module.
+ * ``'multisi'``, - anonymous mc-si- module.
+ * ``'cigs'`` - anonymous copper indium gallium selenide module.
+ * ``'asi'`` - anonymous amorphous silicon module.
+
+ coefficients : array-like, optional
+ user-defined coefficients, if not using one of the default coefficient
+ sets via the ``module_type`` parameter.
+
+ Returns
+ -------
+ mismatch: numeric
+ spectral mismatch factor (unitless) which is multiplied
+ with broadband irradiance reaching a module's cells to estimate
+ effective irradiance, i.e., the irradiance that is converted to
+ electrical current.
+
+ References
+ ----------
+ .. [1] Pelland, S., Beswick, C., Thevenard, D., Côté, A., Pai, A. and 
+ Poissant, Y., 2020, June. Development and testing of the PVSPEC model of 
+ photovoltaic spectral mismatch factor. In 2020 47th IEEE Photovoltaic 
+ Specialists Conference (PVSC) (pp. 1258-1264). IEEE.
+ :doi:`https://doi.org/10.1109/PVSC45281.2020.9300932`
+ """
+# =============================================================================
+# --- Screen Input Data ---
+# =============================================================================
+ #kc
+ kc = np.atleast_1d(clearness_index)
+ kc = kc.astype('float64')
+ if np.min(kc) < 0:
+ raise ValueError('Clearness index cannot be negative')
+ if np.max(kc) > 1:
+ raise ValueError('Clearness index cannot be >1')
+ #ama
+ if np.max(airmass_absolute) > max_airmass_absolute:
+ warn('Exceptionally high air mass: ' +
+ 'values greater than 'f'{max_airmass_absolute} in dataset')
+ # Warn user about exceptionally low ama data
+ if np.min(airmass_absolute) < min_airmass_absolute:
+ airmass_absolute = np.maximum(airmass_absolute, min_airmass_absolute )
+ warn('Exceptionally low air mass: ' +
+ 'model not intended for extra-terrestrial use')
+# =============================================================================
+# --- Default coefficients ---
+# =============================================================================
+ #Empirical coefficients from [1]_
+ _coefficients = {}
+ _coefficients['multisi'] = (
+ 0.9847, -0.05237, 0.03034)
+ _coefficients['monosi'] = (
+ 0.9845, -0.05169, 0.03034)
+ _coefficients['fs-2'] = (
+ 1.002, -0.07108, 0.02465)
+ _coefficients['fs-4'] = (
+ 0.9981, -0.05776, 0.02336)
+ _coefficients['cigs'] = (
+ 0.9791, -0.03904, 0.03096)
+ _coefficients['asi'] = (
+ 1.051, -0.1033, 0.009838)
+ _coefficients['polysi'] = _coefficients['multisi']
+ _coefficients['xsi'] = _coefficients['monosi']
+# =============================================================================
+# --- Check arguments ---
+# =============================================================================
+ if module_type is not None and coefficients is None:
+ coefficients = _coefficients[module_type.lower()]
+ elif module_type is None and coefficients is not None:
+ pass
+ elif module_type is None and coefficients is None:
+ raise ValueError('No valid input provided, both module_type and ' +
+ 'coefficients are None. module_type can be one of ' +
+ 'poly-Si, monosi, fs-2, fs-4, cigs, or asi')
+ else:
+ raise ValueError('Cannot resolve input, must supply only one of ' +
+ 'module_type and coefficients. module_type can be ' +
+ 'one of poly-Si, monosi, fs-2, fs-4, cigs, or asi')
+# =============================================================================
+# --- Specral mismatch calculation ---
+# =============================================================================
+ coeff = coefficients
+ ama = airmass_absolute
+ kc = clearness_index
+ mismatch = coeff[0]*kc**(coeff[1])*ama**(coeff[2])
+
+ return mismatch

pvlib/tests/test_spectrum.py

@@ -315,3 +315,56 @@ def test_spectral_factor_caballero_supplied_ambiguous():
  with pytest.raises(ValueError):
  spectrum.spectral_factor_caballero(1, 1, 1, module_type=None,
  coefficients=None)
+
+@pytest.mark.parametrize("module_type,expected", [
+ ('asi', np.array([1.15534029, 1.1123772, 1.08286684])),
+ ('fs-2', np.array([1.0694323, 1.04948777, 1.03556288])),
+ ('fs-4', np.array([1.05234725, 1.037771, 1.0275516])),
+ ('multisi', np.array([1.03310403, 1.02391703, 1.01744833])),
+ ('monosi', np.array([1.03225083, 1.02335353, 1.01708734])),
+ ('cigs', np.array([1.01475834, 1.01143927, 1.00909094])),
+])
+def test_spectral_factor_pelland(module_type, expected):
+ ams = np.array([1.0, 1.5, 2.0])
+ kcs = np.array([0.4, 0.6, 0.8])
+ out = spectrum.spectral_factor_pelland(ams, kcs,
+ module_type=module_type)
+ assert np.allclose(expected, out, atol=1e-3)
+
+def test_spectral_factor_pelland_supplied():
+ # use the multisi coeffs
+ coeffs = (
+ 0.9847, -0.05237, 0.03034)
+ out = spectrum.spectral_factor_pelland(1.5, 0.8, coefficients=coeffs)
+ expected = 1.00860641
+ assert_allclose(out, expected, atol=1e-3)
+
+def test_spectral_factor_pelland_supplied_redundant():
+ # Error when specifying both module_type and coefficients
+ coeffs = (
+ 0.9847, -0.05237, 0.03034)
+ with pytest.raises(ValueError):
+ spectrum.spectral_factor_pelland(1.5, 0.8, module_type='multisi',
+ coefficients=coeffs)
+
+def test_spectral_factor_pelland_supplied_ambiguous():
+ # Error when specifying neither module_type nor coefficients
+ with pytest.raises(ValueError):
+ spectrum.spectral_factor_pelland(1.5, 0.8, module_type=None,
+ coefficients=None)
+
+def test_spectral_factor_pelland_low_airmass():
+ with pytest.warns(UserWarning, match='Exceptionally low air mass'):
+ _ = spectrum.spectral_factor_pelland(0.1, 0.8, 'multisi') 
+
+def test_spectral_factor_pelland_high_airmass():
+ with pytest.warns(UserWarning, match='Exceptionally high air mass'):
+ _ = spectrum.spectral_factor_pelland(12, 0.8, 'multisi')
+
+def test_spectral_factor_pelland_low_clearnessindex():
+ with pytest.raises(ValueError, match='Clearness index cannot be negative'):
+ _ = spectrum.spectral_factor_pelland(1.5, -0.8, 'multisi') 
+
+def test_spectral_factor_pelland_high_clearnessindex():
+ with pytest.raises(ValueError, match='Clearness index cannot be >1'):
+ _ = spectrum.spectral_factor_pelland(1.5, 1.8, 'multisi')