pvlib iotools—Open-source Python functions for seamless access to solar irradiance data

Jensen, Adam R.; Anderson, Kevin S.; Holmgren, William F.; Mikofski, Mark A.; Hansen, Clifford W.; Boeman, Leland J.; Loonen, Roel

doi:10.1016/j.solener.2023.112092

pvlib iotools—Open-source Python functions for seamless access to solar irradiance data

Journal Article · Fri Nov 03 00:00:00 EDT 2023 · Solar Energy

DOI:https://doi.org/10.1016/j.solener.2023.112092· OSTI ID:2311327

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Technical Univ. of Denmark, Lyngby (Denmark)
Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States)
DNV, Oakland, CA (United States)
Univ. of Arizona, Tucson, AZ (United States)
Eindhoven Univ. of Technology (Netherlands)

Access to accurate solar resource data is critical for numerous applications, including estimating the yield of solar energy systems, developing radiation models, and validating irradiance datasets. However, lack of standardization in data formats and access interfaces across providers constitutes a major barrier to entry for new users. pvlib python’s iotools subpackage aims to solve this issue by providing standardized Python functions for reading local files and retrieving data from external providers. All functions follow a uniform pattern and return convenient data outputs, allowing users to seamlessly switch between data providers and explore alternative datasets. The pvlib package is community-developed on GitHub: https://github.com/pvlib/pvlib-python. As of pvlib python version 0.9.5, the iotools subpackage supports 12 different datasets, including ground measurement, reanalysis, and satellite-derived irradiance data. The supported ground measurement networks include the Baseline Surface Radiation Network (BSRN), NREL MIDC, SRML, SOLRAD, SURFRAD, and the US Climate Reference Network (CRN). Additionally, satellite-derived and reanalysis irradiance data from the following sources are supported: PVGIS (SARAH & ERA5), NSRDB PSM3, and CAMS Radiation Service (including McClear clear-sky irradiance).

View Accepted Manuscript (DOE)

Research Organization:: Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States); Univ. of Arizona, Tucson, AZ (United States)

Sponsoring Organization:: USDOE Office of Energy Efficiency and Renewable Energy (EERE), Renewable Power Office. Solar Energy Technologies Office; USDOE National Nuclear Security Administration (NNSA); Danish Energy Agency (DEA)

Grant/Contract Number:: NA0003525; EE0008214

OSTI ID:: 2311327

Report Number(s):: SAND--2023-13720J

Journal Information:: Solar Energy, Journal Name: Solar Energy Vol. 266; ISSN 0038-092X

Publisher:: ElsevierCopyright Statement

Country of Publication:: United States

Language:: English

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