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Added module types to pvl_FSspeccorr (#10)
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* Updated pvl_FSspeccorr to include coefficients for CIGS and amorphus silicon modules

* fixed indent on line 163

* Updated reference list for pvl_FSspeccor.m to include additional testing and validation. Reference also includes the SR of CIGS and a-Si modules used to derive coefficients.
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@MLEEFS @cwhanse
MLEEFS authored and cwhanse committed Feb 7, 2017
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Showing 1 changed file with 64 additions and 45 deletions.
109 changes: 64 additions & 45 deletions pvl_FSspeccorr.m
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function [M] = pvl_FSspeccorr(Pwat,AMa,varargin)
% pvl_FSspeccorr Spectral mismatch modifier based on precipitable water and
% pvl_FSspeccorr Spectral mismatch modifier based on precipitable water and
% absolute (pressure corrected) airmass.
%
%
% Syntax:
% [M] = pvl_FSspeccorr(Pwat, AMa, pvModType)
% [M] = pvl_FSspeccorr(Pwat, AMa, pvModType)
% [M] = pvl_FSspeccorr(Pwat, AMa, custCoeff)
%
% Description:
%
% Estimates a spectral mismatch modifier M representing the effect on
% module short circuit current of variation in the spectral irradiance.
%
% Estimates a spectral mismatch modifier M representing the effect on
% module short circuit current of variation in the spectral irradiance.
% M is estimated from absolute (pressure currected) air mass, AMa, and
% precipitable water, Pwat, using the following function:
%
% M = coeff(1) + coeff(2)*AMa + coeff(3)*Pwat + coeff(4)*AMa.^.5
% + coeff(5)*Pwat.^.5 + coeff(6)*AMa./Pwat.^0.5 (1)
% M = coeff(1) + coeff(2)*AMa + coeff(3)*Pwat + coeff(4)*AMa.^.5
% + coeff(5)*Pwat.^.5 + coeff(6)*AMa./Pwat.^0.5 (1)
%
% Default coefficients are determined for several cell types with
% known quantum efficiency curves, by using the Simple Model of the
% Atmospheric Radiative Transfer of Sunshine (SMARTS) [1].
% Using SMARTS, spectrums are simulated with all combinations of AMa
% Default coefficients are determined for several cell types with
% known quantum efficiency curves, by using the Simple Model of the
% Atmospheric Radiative Transfer of Sunshine (SMARTS) [1].
% Using SMARTS, spectrums are simulated with all combinations of AMa
% and Pwat where:
% * 0.1 cm <= Pwat <= 5 cm
% * 1.0 <= AMa <= 5
% * 1.0 <= AMa <= 5
% * Spectral range is limited to that of CMP11 (280 nm to 2800 nm)
% * spectrum simulated on a plane normal to the sun
% * All other parameters fixed at G173 standard
% From these simulated spectra, M is calculated using the known quantum
% efficiency curves. Multiple linear regression is then applied to fit
% From these simulated spectra, M is calculated using the known quantum
% efficiency curves. Multiple linear regression is then applied to fit
% Eq. 1 to determine the coefficients for each module.
%
% Function pvl_FSspeccorr was developed by Mitchell Lee and Alex Panchula,
% at First Solar, 2015. Detailed description of spectral correction
% can be found in [2]
% at First Solar, 2015. Detailed description of the spectral correction
% can be found in [2]. Additional validation and testing of the model
% can be found in [3].
%
% Inputs:
% Pwat - atmospheric precipitable water (cm). Can be
% entered as a vector.
% AMa - absolute (pressure corrected) airmass, as a vector of the same
% AMa - absolute (pressure corrected) airmass, as a vector of the same
% length as Pwat
% pvModType - a string specifying a cell type. Can be lower or upper case
% pvModType - a string specifying a cell type. Can be lower or upper case
% letters. Admits values of 'cdte', 'monosi'='xsi', 'multisi'='polysi'.
% If provided, this input
% selects coefficients for the following default modules:
% 'cdte' - coefficients for First Solar Series 4-2 CdTe modules.
% 'cdte' - coefficients for First Solar Series 4-2 CdTe modules.
% 'monosi','xsi' - coefficients for First Solar TetraSun modules.
% 'multisi','polysi' - coefficients for multi-crystalline silicon
% 'multisi','polysi' - coefficients for multi-crystalline silicon
% modules. The module used to calculate the spectral
% correction coefficients corresponds to the Mult-crystalline
% silicon Manufacturer 2 Model C from [3].
% correction coefficients corresponds to the Mult-crystalline
% silicon Manufacturer 2 Model C from [4].
% 'cigs' - coefficients for anonymous copper indium gallium selenide
% PV module. Lower and upper limits of QE are 350 nm and 1300 nm,
% respectively. Please note that the QE of CIGS modules
% can vary significantly depending on the PV manufacture and
% vintage. Spectral Response of module module used to derive
% CIGS coefficients can be found in [3].
% 'asi' - coefficients for anonymous amorphous silicon PV module.
% Lower and upper limits of QE are 280 nm and 800 nm,
% respectively. Please note that the QE of a-Si modules
% can vary significantly depending on the PV manufacture and
% vintage. Spectral Response of module module used to derive
% a-Si coefficients can be found in [3].
% custCoeff - allows for entry of user defined spectral correction
% coefficients. Coefficients must be entered as a numeric row or
% column vector of length 6. Derivation of coefficients requires use
% of SMARTS and PV module quantum efficiency curve. Useful for modeling
% coefficients. Coefficients must be entered as a numeric row or
% column vector of length 6. Derivation of coefficients requires use
% of SMARTS and PV module quantum efficiency curve. Useful for modeling
% PV module types which are not included as defaults, or to fine tune
% the spectral correction to a particular mono-Si, multi-Si, or CdTe
% the spectral correction to a particular mono-Si, multi-Si, or CdTe
% PV module. Note that the parameters for modules with very
% similar QE should be similar, in most cases limiting the need for
% module specific coefficients.
Expand All @@ -67,19 +80,21 @@
% to electrical current.
%
% References:
% [1] Gueymard, Christian. SMARTS2: a simple model of the atmospheric
% radiative transfer of sunshine: algorithms and performance
% [1] Gueymard, Christian. SMARTS2: a simple model of the atmospheric
% radiative transfer of sunshine: algorithms and performance
% assessment. Cocoa, FL: Florida Solar Energy Center, 1995.
% [2] Lee, Mitchell, and Panchula, Alex. "Spectral Correction for
% Photovoltaic Module Performance Based on Air Mass and Precipitable
% Water." IEEE Photovoltaic Specialists Conference, Portland, 2016
% [3] Marion, William F., et al. User's Manual for Data for Validating
% Photovoltaic Module Performance Based on Air Mass and Precipitable
% Water." IEEE Photovoltaic Specialists Conference, Portland, 2016
% [3] Schweiger, M. and Hermann, W, Influence of Spectral Effects on
% Energy Yield of Different PV Modules: Comparison of Pwat and
% MMF Approach, TUV Rheinland Energy GmbH report 21237296.003, January 2017
% [4] Marion, William F., et al. User's Manual for Data for Validating
% Models for PV Module Performance. National Renewable Energy Laboratory, 2014.
% http://www.nrel.gov/docs/fy14osti/61610.pdf



% Correct for AMa and Pwat having transposed dimensions
% Correct for AMa and Pwat having transposed dimensions
if isrow(AMa)
AMa = AMa';
end
Expand Down Expand Up @@ -108,17 +123,17 @@
% *** AMa ***
% Replace Extremely High AM with AM 10 to prevent model divergence
% AM > 10 will only occur very close to sunset
if max(AMa) > 10
AMa(AMa > 10) = 10;
if max(AMa) > 10
AMa(AMa > 10) = 10;
end

% Warn user about AMa data that is exceptionally low
if min(AMa) < 0.58
warning(['Exceptionally low air mass: ',...
'model not intended for extra-terrestrial use'])
% pvl_absoluteairmass(1,pvl_alt2pres(4340)) = 0.58
% Elevation of Mina Pirquita, Argentian = 4340 m. Highest elevation city
% with population over 50,000.
warning(['Exceptionally low air mass: ',...
'model not intended for extra-terrestrial use'])
% pvl_absoluteairmass(1,pvl_alt2pres(4340)) = 0.58
% Elevation of Mina Pirquita, Argentian = 4340 m. Highest elevation city
% with population over 50,000.
end

% If user input is a character array, use appropriate default coefficients.
Expand All @@ -131,22 +146,26 @@
% For modeling the performance of earlier CdTe module series,
% use the coefficients that are commented out
% [0.79418,-0.049883,-0.013402,0.16766,0.083377,-0.0044007];
coeff = [0.86273, -0.038948, -0.012506, 0.098871, 0.084658, -0.0042948];
coeff = [0.86273, -0.038948, -0.012506, 0.098871, 0.084658, -0.0042948];
case {'monosi','xsi'}
% Coefficients for First Solar TetraSun Modules
coeff = [0.85914, -0.020880, -0.0058853, 0.12029, 0.026814, -0.0017810];
coeff = [0.85914, -0.020880, -0.0058853, 0.12029, 0.026814, -0.0017810];
case {'polysi','multisi'}
% Coefficients for Multi-Si: Manufacturer 2 Model C
coeff = [0.84090, -0.027539, -0.0079224, 0.13570, 0.038024, -0.0021218];
case 'cigs'
coeff = [0.85252, -0.022314, -0.0047216, 0.13666, 0.013342, -0.0008945];
case 'asi'
coeff = [1.12094, -0.047620, -0.0083627, -0.10443, 0.098382,-0.0033818];
otherwise
error('Incorrect module type for use of default parameters')
end
% User input coefficients
% User input coefficients
else
coeff = varargin{1};
end

% Evaluate Spectral Shift
M = coeff(1) + coeff(2)*AMa + coeff(3)*Pwat + coeff(4)*AMa.^.5 + coeff(5)*Pwat.^.5 + coeff(6)*AMa./Pwat.^0.5;
M = coeff(1) + coeff(2)*AMa + coeff(3)*Pwat + coeff(4)*AMa.^.5 + coeff(5)*Pwat.^.5 + coeff(6)*AMa./Pwat.^0.5;
end

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