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pvlib-python is a community-developed toolbox that provides a set of functions and classes for simulating the performance of photovoltaic energy systems and accomplishing related tasks. The core mission of pvlib-python is to provide open, reliable, interoperable, and thoroughly-tested implementations of PV system models for researchers, engineers, and analysts working in the solar energy field. Our goal is to make photovoltaic modeling accessible and reproducible for everyone.

Full documentation can be found at pvlib-python ReadTheDocs, including a comprehensive Frequently Asked Questions page.

pvlib-python releases may be installed using the pip and conda tools:

# Using pip
pip install pvlib

# Using conda
conda install -c conda-forge pvlib

Please see the Installation page of the documentation for complete instructions.

We welcome your help to make pvlib-python an even better tool! Whether you're fixing bugs, adding new features, improving documentation, or sharing examples, your contributions are valuable to our community.

Please see the Contributing page for more on how you can contribute. We welcome contributions of all kinds, including:

• Code improvements and bug fixes
• Documentation enhancements
• New models and features
• Example notebooks and tutorials
• Testing improvements

The long-term success of pvlib-python depends on substantial community support and involvement.

Many of the contributors to pvlib-python work in institutions where citation metrics are used in performance or career evaluations. If you use pvlib-python in a published work, please cite:

Anderson, K., Hansen, C., Holmgren, W., Jensen, A., Mikofski, M., and Driesse, A. "pvlib-python: 2023 project update." Journal of Open Source Software, 8(92), 5994, (2023). https://doi.org/10.21105/joss.05994

Jensen, A., Anderson, K., Holmgren, W., Mikofski, M., Hansen, C., Boeman, L., Loonen, R. "pvlib iotools — Open-source Python functions for seamless access to solar irradiance data." Solar Energy, 266, 112092, (2023). https://doi.org/10.1016/j.solener.2023.112092

Holmgren, W., Hansen, C., and Mikofski, M. "pvlib-python: a python package for modeling solar energy systems." Journal of Open Source Software, 3(29), 884, (2018). https://doi.org/10.21105/joss.00884

If you use pvlib-python in a commercial or publicly-available application, please consider displaying one of the "powered by pvlib" logos shown below:

pvlib usage questions can be asked on Stack Overflow and should be tagged with the pvlib tag.

The pvlib-python google group is used for discussing various topics of interest to the pvlib-python community. We also make new version announcements on the google group.

If you suspect that you may have discovered a bug, would like to suggest an enhancement, or propose a new feature for pvlib, please create an issue on our GitHub issues page. When creating an issue:

• For bugs: Include a minimal code example that reproduces the problem
• For enhancements: Describe the desired functionality and why it would be valuable
• For new features: Outline the feature and its potential use cases

Be sure to include relevant details that will help maintainers understand and address your request.

pvlib-python is released under the BSD 3-clause license, a permissive open source license that allows for commercial and private use with limited restrictions. See the LICENSE file for complete details.

pvlib-python began in 2013 as a Python translation of the PVLIB for Matlab toolbox developed by Sandia National Laboratories. pvlib-python has grown substantially since then. Today it contains code contributions from over a hundred individuals worldwide and is maintained by a core group of PV modelers from a variety of institutions.

pvlib has been supported directly and indirectly by DOE, NumFOCUS, and Google Summer of Code funding, university research projects, companies that allow their employees to contribute, and from personal time.

pvlib-python is a NumFOCUS Affiliated Project.