Source code for pvlib.shading

"""
The ``shading`` module contains functions that model module shading and the
associated effects on PV module output
"""

import numpy as np
import pandas as pd
from pvlib.tools import sind, cosd


[docs]def masking_angle(surface_tilt, gcr, slant_height): """ The elevation angle below which diffuse irradiance is blocked. The ``height`` parameter determines how far up the module's surface to evaluate the masking angle. The lower the point, the steeper the masking angle [1]_. SAM uses a "worst-case" approach where the masking angle is calculated for the bottom of the array (i.e. ``slant_height=0``) [2]_. Parameters ---------- surface_tilt : numeric Panel tilt from horizontal [degrees]. gcr : float The ground coverage ratio of the array [unitless]. slant_height : numeric The distance up the module's slant height to evaluate the masking angle, as a fraction [0-1] of the module slant height [unitless]. Returns ------- mask_angle : numeric Angle from horizontal where diffuse light is blocked by the preceding row [degrees]. See Also -------- masking_angle_passias sky_diffuse_passias References ---------- .. [1] D. Passias and B. Källbäck, "Shading effects in rows of solar cell panels", Solar Cells, Volume 11, Pages 281-291. 1984. DOI: 10.1016/0379-6787(84)90017-6 .. [2] Gilman, P. et al., (2018). "SAM Photovoltaic Model Technical Reference Update", NREL Technical Report NREL/TP-6A20-67399. Available at https://www.nrel.gov/docs/fy18osti/67399.pdf """ # The original equation (8 in [1]) requires pitch and collector width, # but it's easy to non-dimensionalize it to make it a function of GCR # by factoring out B from the argument to arctan. numerator = (1 - slant_height) * sind(surface_tilt) denominator = 1/gcr - (1 - slant_height) * cosd(surface_tilt) phi = np.arctan(numerator / denominator) return np.degrees(phi)
[docs]def masking_angle_passias(surface_tilt, gcr): r""" The average masking angle over the slant height of a row. The masking angle is the angle from horizontal where the sky dome is blocked by the row in front. The masking angle is larger near the lower edge of a row than near the upper edge. This function calculates the average masking angle as described in [1]_. Parameters ---------- surface_tilt : numeric Panel tilt from horizontal [degrees]. gcr : float The ground coverage ratio of the array [unitless]. Returns ---------- mask_angle : numeric Average angle from horizontal where diffuse light is blocked by the preceding row [degrees]. See Also -------- masking_angle sky_diffuse_passias Notes ----- The pvlib-python authors believe that Eqn. 9 in [1]_ is incorrect. Here we use an independent equation. First, Eqn. 8 is non-dimensionalized (recasting in terms of GCR): .. math:: \psi(z') = \arctan \left [ \frac{(1 - z') \sin \beta} {\mathrm{GCR}^{-1} + (z' - 1) \cos \beta} \right ] Where :math:`GCR = B/C` and :math:`z' = z/B`. The average masking angle :math:`\overline{\psi} = \int_0^1 \psi(z') \mathrm{d}z'` is then evaluated symbolically using Maxima (using :math:`X = 1/\mathrm{GCR}`): .. code-block:: none load(scifac) /* for the gcfac function */ assume(X>0, cos(beta)>0, cos(beta)-X<0); /* X is 1/GCR */ gcfac(integrate(atan((1-z)*sin(beta)/(X+(z-1)*cos(beta))), z, 0, 1)) This yields the equation implemented by this function: .. math:: \overline{\psi} = \ &-\frac{X}{2} \sin\beta \log | 2 X \cos\beta - (X^2 + 1)| \\ &+ (X \cos\beta - 1) \arctan \frac{X \cos\beta - 1}{X \sin\beta} \\ &+ (1 - X \cos\beta) \arctan \frac{\cos\beta}{\sin\beta} \\ &+ X \log X \sin\beta The pvlib-python authors have validated this equation against numerical integration of :math:`\overline{\psi} = \int_0^1 \psi(z') \mathrm{d}z'`. References ---------- .. [1] D. Passias and B. Källbäck, "Shading effects in rows of solar cell panels", Solar Cells, Volume 11, Pages 281-291. 1984. DOI: 10.1016/0379-6787(84)90017-6 """ # wrap it in an array so that division by zero is handled well beta = np.radians(np.array(surface_tilt)) sin_b = np.sin(beta) cos_b = np.cos(beta) X = 1/gcr with np.errstate(divide='ignore', invalid='ignore'): # ignore beta=0 term1 = -X * sin_b * np.log(np.abs(2 * X * cos_b - (X**2 + 1))) / 2 term2 = (X * cos_b - 1) * np.arctan((X * cos_b - 1) / (X * sin_b)) term3 = (1 - X * cos_b) * np.arctan(cos_b / sin_b) term4 = X * np.log(X) * sin_b psi_avg = term1 + term2 + term3 + term4 # when beta=0, divide by zero makes psi_avg NaN. replace with 0: psi_avg = np.where(np.isfinite(psi_avg), psi_avg, 0) if isinstance(surface_tilt, pd.Series): psi_avg = pd.Series(psi_avg, index=surface_tilt.index) return np.degrees(psi_avg)
[docs]def sky_diffuse_passias(masking_angle): r""" The diffuse irradiance loss caused by row-to-row sky diffuse shading. Even when the sun is high in the sky, a row's view of the sky dome will be partially blocked by the row in front. This causes a reduction in the diffuse irradiance incident on the module. The reduction depends on the masking angle, the elevation angle from a point on the shaded module to the top of the shading row. In [1]_ the masking angle is calculated as the average across the module height. SAM assumes the "worst-case" loss where the masking angle is calculated for the bottom of the array [2]_. This function, as in [1]_, makes the assumption that sky diffuse irradiance is isotropic. Parameters ---------- masking_angle : numeric The elevation angle below which diffuse irradiance is blocked [degrees]. Returns ------- derate : numeric The fraction [0-1] of blocked sky diffuse irradiance. See Also -------- masking_angle masking_angle_passias References ---------- .. [1] D. Passias and B. Källbäck, "Shading effects in rows of solar cell panels", Solar Cells, Volume 11, Pages 281-291. 1984. DOI: 10.1016/0379-6787(84)90017-6 .. [2] Gilman, P. et al., (2018). "SAM Photovoltaic Model Technical Reference Update", NREL Technical Report NREL/TP-6A20-67399. Available at https://www.nrel.gov/docs/fy18osti/67399.pdf """ return 1 - cosd(masking_angle/2)**2