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references, table format, updated text
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‎docs/sphinx/source/user_guide/spectrum.rst‎

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@@ -15,32 +15,66 @@ demonstrating the application of three pvlib-python spectral mismatch models
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is also available: :ref:`sphx_glr_gallery_spectrum_spectral_factor.py`. Here,
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a comparison of all models available in pvlib-python is presented. An extended
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review of a wider range of models available in the published literature may be
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found in Reference [X].
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found in Reference [1]_.
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The table below summarises the models currently available in pvlib, the inputs
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required, cell technologies for which model coefficients have been published,
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source of data used for model development and validation, and references.
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and references. Note that while most models are validated for specific cell
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technologies, the Sandia Array Performance Model (SAPM) and spectral mismatch
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calculation are not specific to cell type; the former is validated for a range
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of commerical module products.
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+---------------------------------------------------------+--------------------------------------------------------------+-----------------+------------+
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| Model | Inputs | Cell technology | Reference |
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+=========================================================+==============================================================+=================+============+
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| :py:func:`~pvlib.spectrum.spectral_factor_caballero` | absolute airmass, precipitable water, aerosol optical depth | CdTe, mono-Si, | |
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| | | poly-Si, CIGS, | [X] |
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| :py:func:`~pvlib.spectrum.spectral_factor_caballero` | absolute airmass, | CdTe, | |
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| | precipitable water, | mono-Si, | |
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| | aerosol optical depth | poly-Si, CIGS, | [2]_ |
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| | | aSi, perovskite | |
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+---------------------------------------------------------+--------------------------------------------------------------+-----------------+------------+
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| :py:func:`~pvlib.spectrum.spectral_factor_firstsolar` | absolute airmass, precipitable water | mSi, CdTe | [X] |
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| :py:func:`~pvlib.spectrum.spectral_factor_firstsolar` | absolute airmass, | CdTe, | |
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| | precipitable water | poly-Si | [3]_ |
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+---------------------------------------------------------+--------------------------------------------------------------+-----------------+------------+
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| :py:func:`~pvlib.spectrum.spectral_factor_sapm` | absolute airmass | Multiple | [X] |
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| :py:func:`~pvlib.spectrum.spectral_factor_sapm` | absolute airmass | Multiple | [4]_ |
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+---------------------------------------------------------+--------------------------------------------------------------+-----------------+------------+
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| :py:func:`~pvlib.spectrum.spectral_factor_pvspec` | absolute airmass, clearsky index | CdTe, mono-Si, | |
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| | | poly-Si, CIGS, | [X] |
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| :py:func:`~pvlib.spectrum.spectral_factor_pvspec` | absolute airmass, | CdTe, | |
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| | clearsky index | poly-Si, | |
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| | | mono-Si, | |
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| | | CIGS, | [5]_ |
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| | | aSi | |
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+---------------------------------------------------------+--------------------------------------------------------------+-----------------+------------+
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| :py:func:`~pvlib.spectrum.spectral_factor_jrc` | absolute airmass, clearsky index | CdTe, poly-Si | [X] |
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| :py:func:`~pvlib.spectrum.spectral_factor_jrc` | absolute airmass, clearsky index | CdTe, | |
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| | | poly-Si | [6]_ |
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+---------------------------------------------------------+--------------------------------------------------------------+-----------------+------------+
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| :py:func:`~pvlib.spectrum.calc_spectral_mismatch_field` | spectral response, spectral irradiance | - | [X] |
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| :py:func:`~pvlib.spectrum.calc_spectral_mismatch_field` | spectral response, spectral irradiance | - | [7]_ |
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+---------------------------------------------------------+--------------------------------------------------------------+-----------------+------------+
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References
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----------
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.. [1] R. Daxini and Y. Wu, "Review of methods to account for the solar
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spectral influence on photovoltaic device performance," Energy,
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vol. 286, p. 129461, Jan. 2024. :doi:`10.1016/j.energy.2023.129461`
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.. [2] J. A. Caballero, E. Fernández, M. Theristis, F. Almonacid, and
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G. Nofuentes, "Spectral Corrections Based on Air Mass, Aerosol Optical
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Depth and Precipitable Water for PV Performance Modeling," IEEE Journal
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of Photovoltaics, vol. 8, no. 2, pp. 552–558, Mar. 2018.
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:doi:`10.1109/JPHOTOV.2017.2787019`
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.. [3] M. Lee and A. Panchula, "Spectral Correction for Photovoltaic Module
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Performance Based on Air Mass and Precipitable Water," 2016 IEEE 43rd
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Photovoltaic Specialists Conference (PVSC), Portland, OR, USA, 2016,
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pp. 3696-3699. :doi:`10.1109/PVSC.2016.7749836`
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.. [4] D. L. King, W. E. Boyson, and J. A. Kratochvil, Photovoltaic Array
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Performance Model, Sandia National Laboratories, Albuquerque, NM, USA,
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Tech. Rep. SAND2004-3535, Aug. 2004. :doi:`10.2172/919131`
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.. [5] S. Pelland, J. Remund, and J. Kleissl, "Development and Testing of the
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PVSPEC Model of Photovoltaic Spectral Mismatch Factor," in Proc. 2020
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IEEE 47th Photovoltaic Specialists Conference (PVSC), Calgary, AB,
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Canada, 2020, pp. 1–6. :doi:`10.1109/PVSC45281.2020.9300932`
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.. [6] T. Huld, T. C. Sample, and E. D. Dunlop, "A Simple Model for Estimating
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the Influence of Spectral Variations on the Performance of PV Modules,
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"AerosolSolar Energy Materials and Solar Cells, vol. 92, no. 12,
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pp. 1645–1656, Dec. 2008. :doi:`10.1016/j.solmat.2008.07.016`
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.. [7] IEC 60904-7:2019, Photovoltaic devices — Part 7: Computation of the
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spectral mismatch correction for measurements of photovoltaic devices,
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International Electrotechnical Commission, Geneva, Switzerland, 2019.

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