GSEE is a solar energy simulation library designed for rapid calculations and ease of use. It can run for a single site with a pandas DataFrame to hundreds of thousands of sites or global grids with xarray Datasets. Renewables.ninja uses GSEE.
The development of GSEE predates the existence of pvlib-python but builds on its functionality as of v0.4.0. Use GSEE if you want fast simulations with sensible defaults and/or its climate data interface, and pvlib-python if you need control over the nuts and bolts of simulating PV systems.
pip install gsee
To also install the built-in irradiance probability density functions used by the climate data interface:
pip install gsee[climate]
GSEE is also available via conda-forge.
See the documentation for more information on GSEE's functionality and for examples.
Contact Stefan Pfenninger for questions about GSEE. GSEE is also a component of the Renewables.ninja project, developed by Stefan Pfenninger and Iain Staffell. Use the contact page there if you want more information about Renewables.ninja.
If you use GSEE or code derived from it in academic work, please cite:
Stefan Pfenninger and Iain Staffell (2016). Long-term patterns of European PV output using 30 years of validated hourly reanalysis and satellite data. Energy 114, pp. 1251-1265. doi: 10.1016/j.energy.2016.08.060
BSD-3-Clause
Thanks goes to these wonderful people (emoji key):
 Stefan Pfenninger-Lee 💻 🤔 |
 Iain Staffell 🤔 |
 Johannes 💻 🤔 |
 Tony Yu Cao 🐛 |
 Jan Wohland 🐛 |
 Linh Ho 💻 🤔 |
 Mayk Thewessen 💻 |
This project follows the all-contributors specification. Contributions of any kind welcome!