Add spectral mismatch model comparison table

docs/sphinx/source/user_guide/index.rst

@@ -21,6 +21,7 @@ This user guide is an overview and explains some of the key features of pvlib.
    modeling_topics/pvsystem
    modeling_topics/modelchain
    modeling_topics/timetimezones
+   modeling_topics/spectrum
    modeling_topics/bifacial
    modeling_topics/clearsky
    modeling_topics/weather_data

docs/sphinx/source/user_guide/modeling_topics/spectrum.rst

@@ -0,0 +1,97 @@
+.. _spectrum_user_guide:
+
+Spectrum
+========
+
+The spectrum functionality of pvlib-python includes simulating clear sky
+spectral irradiance curves, calculating the spectral mismatch factor for
+a range of single-junction PV cell technologies, and other calculations
+such as converting between spectral response and EQE, and computing average
+photon energy values from spectral irradiance data.
+
+This user guide page summarizes some of pvlib-python's spectrum-related
+capabilities, starting with a summary of spectral mismatch estimation models
+available in pvlib-python.
+
+Spectral mismatch models
+------------------------
+
+pvlib-python contains several models to estimate the spectral mismatch factor
+using atmospheric variables such as air mass, or system and meteorological
+data such as spectral response and spectral irradiance. Two separate examples
+demonstrating the application of four pvlib-python spectral mismatch models
+are also available: :ref:`sphx_glr_gallery_spectrum_spectral_factor.py` and
+Reference [1]_, the latter of which also contains downloadable spectral
+response and spectral irradiance data. On this page, a comparison of all models
+available in pvlib-python is presented. An extended review of a wider range of
+models available in the published literature may be found in Reference [2]_.
+
+The table below summarises the models currently available in pvlib, the inputs
+required, cell technologies for which model coefficients have been published, 
+and references. Note that while most models are validated for specific cell
+technologies, the Sandia Array Performance Model (SAPM) and spectral mismatch
+calculation are not specific to cell type; the former is validated for a range
+of commerical module products.
+
++---------------------------------------------------------+----------------------------+-----------------+-----------+
+| Model                                                   | Inputs                     | Cell technology | Reference |
++=========================================================+============================+=================+===========+
+| :py:func:`~pvlib.spectrum.spectral_factor_caballero`    | :term:`absolute_airmass`,  | CdTe,           |           |
+|                                                         | :term:`precipitable_water`,| mono-Si,        |           |
+|                                                         | aerosol optical depth      | poly-Si,        | [3]_      |
+|                                                         |                            | aSi,            |           |
+|                                                         |                            | CIGS,           |           |
+|                                                         |                            | Perovskite      |           |
++---------------------------------------------------------+----------------------------+-----------------+-----------+
+| :py:func:`~pvlib.spectrum.spectral_factor_firstsolar`   | :term:`absolute_airmass`,  | CdTe,           |           |
+|                                                         | :term:`precipitable_water` | poly-Si         | [4]_      |
++---------------------------------------------------------+----------------------------+-----------------+-----------+
+| :py:func:`~pvlib.spectrum.spectral_factor_sapm`         | :term:`absolute_airmass`   | Multiple        | [5]_      |
++---------------------------------------------------------+----------------------------+-----------------+-----------+
+| :py:func:`~pvlib.spectrum.spectral_factor_pvspec`       | :term:`absolute_airmass`,  | CdTe,           |           |
+|                                                         | clearsky index             | poly-Si,        |           |
+|                                                         |                            | mono-Si,        |           |
+|                                                         |                            | CIGS,           | [6]_      |
+|                                                         |                            | aSi             |           |
++---------------------------------------------------------+----------------------------+-----------------+-----------+
+| :py:func:`~pvlib.spectrum.spectral_factor_jrc`          | :term:`relative_airmass`,  | CdTe,           |           |
+|                                                         | clearsky index             | poly-Si         | [7]_      |
++---------------------------------------------------------+----------------------------+-----------------+-----------+
+| :py:func:`~pvlib.spectrum.calc_spectral_mismatch_field` | spectral response,         | Any single      |           |
+|                                                         | :term:`spectra`            | junction        |           |
++---------------------------------------------------------+----------------------------+-----------------+-----------+
+
+
+References
+----------
+.. [1] A. Driesse, J. S. Stein, and M. Theristis, "Global horizontal spectral
+       irradiance and module spectral response measurements: an open dataset
+       for PV research Sandia National Laboratories, ALbuquerque, NM, USA, Rep.
+       SAND2023-02045, 2023. Available:
+       https://datahub.duramat.org/dataset/module-sr-library
+
+.. [2] R. Daxini and Y. Wu, "Review of methods to account for the solar
+       spectral influence on photovoltaic device performance," Energy, 
+       vol. 286, p. 129461, Jan. 2024. :doi:`10.1016/j.energy.2023.129461`
+.. [3] J. A. Caballero, E. Fernández, M. Theristis, F. Almonacid, and
+       G. Nofuentes, "Spectral Corrections Based on Air Mass, Aerosol Optical
+       Depth and Precipitable Water for PV Performance Modeling," IEEE Journal
+       of Photovoltaics, vol. 8, no. 2, pp. 552–558, Mar. 2018. 
+       :doi:`10.1109/JPHOTOV.2017.2787019`
+.. [4] M. Lee and A. Panchula, "Spectral Correction for Photovoltaic Module
+       Performance Based on Air Mass and Precipitable Water," 2016 IEEE 43rd
+       Photovoltaic Specialists Conference (PVSC), Portland, OR, USA, 2016,
+       pp. 3696-3699. :doi:`10.1109/PVSC.2016.7749836`
+.. [5] D. L. King, W. E. Boyson, and J. A. Kratochvil, Photovoltaic Array
+       Performance Model, Sandia National Laboratories, Albuquerque, NM, USA,
+       Tech. Rep. SAND2004-3535, Aug. 2004. :doi:`10.2172/919131`
+.. [6] S. Pelland, J. Remund, and J. Kleissl, "Development and Testing of the
+       PVSPEC Model of Photovoltaic Spectral Mismatch Factor," in Proc. 2020
+       IEEE 47th Photovoltaic Specialists Conference (PVSC), Calgary, AB,
+       Canada, 2020, pp. 1–6. :doi:`10.1109/PVSC45281.2020.9300932`
+.. [7] H. Thomas, S. Tony, and D. Ewan, “A Simple Model for Estimating the
+       Influence of Spectrum Variations on PV Performance,” pp. 3385–3389, Nov.
+       2009, :doi:10.4229/24THEUPVSEC2009-4AV.3.27
+.. [8] IEC 60904-7:2019, Photovoltaic devices — Part 7: Computation of the
+       spectral mismatch correction for measurements of photovoltaic devices, 
+       International Electrotechnical Commission, Geneva, Switzerland, 2019.