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.. _spectrum_user_guide: | ||
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Spectrum | ||
======== | ||
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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. | ||
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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. | ||
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Spectral mismatch models | ||
------------------------ | ||
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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. An example | ||
demonstrating the application of three pvlib-python spectral mismatch models | ||
is also available: :ref:`sphx_glr_gallery_spectrum_spectral_factor.py`. Here, | ||
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 [1]_. | ||
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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. | ||
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+---------------------------------------------------------+--------------------------------------------------------------+-----------------+------------+ | ||
| Model | Inputs | Cell technology | Reference | | ||
+=========================================================+==============================================================+=================+============+ | ||
| :py:func:`~pvlib.spectrum.spectral_factor_caballero` | absolute airmass, | CdTe, | | | ||
| | precipitable water, | mono-Si, | | | ||
| | aerosol optical depth | poly-Si, CIGS, | [2]_ | | ||
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| | | aSi, perovskite | | | ||
+---------------------------------------------------------+--------------------------------------------------------------+-----------------+------------+ | ||
| :py:func:`~pvlib.spectrum.spectral_factor_firstsolar` | absolute airmass, | CdTe, | | | ||
| | precipitable water | poly-Si | [3]_ | | ||
+---------------------------------------------------------+--------------------------------------------------------------+-----------------+------------+ | ||
| :py:func:`~pvlib.spectrum.spectral_factor_sapm` | absolute airmass | Multiple | [4]_ | | ||
+---------------------------------------------------------+--------------------------------------------------------------+-----------------+------------+ | ||
| :py:func:`~pvlib.spectrum.spectral_factor_pvspec` | absolute airmass, | CdTe, | | | ||
| | clearsky index | poly-Si, | | | ||
| | | mono-Si, | | | ||
| | | CIGS, | [5]_ | | ||
| | | aSi | | | ||
+---------------------------------------------------------+--------------------------------------------------------------+-----------------+------------+ | ||
| :py:func:`~pvlib.spectrum.spectral_factor_jrc` | absolute airmass, clearsky index | CdTe, | | | ||
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| | | poly-Si | [6]_ | | ||
+---------------------------------------------------------+--------------------------------------------------------------+-----------------+------------+ | ||
| :py:func:`~pvlib.spectrum.calc_spectral_mismatch_field` | spectral response, spectral irradiance | - | [7]_ | | ||
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+---------------------------------------------------------+--------------------------------------------------------------+-----------------+------------+ | ||
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References | ||
---------- | ||
.. [1] 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` | ||
.. [2] 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` | ||
.. [3] 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` | ||
.. [4] 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` | ||
.. [5] 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` | ||
.. [6] T. Huld, T. C. Sample, and E. D. Dunlop, "A Simple Model for Estimating | ||
the Influence of Spectral Variations on the Performance of PV Modules, | ||
"AerosolSolar Energy Materials and Solar Cells, vol. 92, no. 12, | ||
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 | ||
spectral mismatch correction for measurements of photovoltaic devices, | ||
International Electrotechnical Commission, Geneva, Switzerland, 2019. |
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