Projects and publications that use pvlib python

Please add a link and a brief description for projects or publications that use pvlib-python. We keep the list in reverse chronological order.

The preferred citation for pvlib python is

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

Link to Google scholar citations of Holmgren, Hansen, and Mikofski (2018).

2020

Simulation of multi-annual time series of solar photovoltaic power: Is the ERA5-land reanalysis the next big step?. L. Ramirez-Camargo et al., Sustainable Energy Technologies and Assessments, 42, 100829 (2020). doi: 10.1016/j.seta.2020.100829

Evaluation of statistical learning configurations for gridded solar irradiance forecasting. D. Gagne et al., Solar Energy, 157, 383-393 (2017). doi: 10.1016/j.solener.2017.04.031
Optimal interpolation of satellite and ground data for irradiance nowcasting at city scales. A. Lorenzo et al. Solar Energy, 144, 466 (2017). doi: 10.1016/j.solener.2017.01.038
An Open Source Solar Power Forecasting Tool Using PVLIB Python. W. Holmgren et al. American Meteorological Society Conference. January, 2017. pdf
Utility Scale Solar and Wind Power Variability in the Southwest United States. W. Holmgren et al. American Meteorological Society Conference. January, 2017. pdf
nabu: A distributed, parallel, data processing platform. A. Lorenzo et al. American Meteorological Society Conference. January, 2017. pdf

PVLIB: Open Source Photovoltaic Performance Modeling Functions for Matlab and Python. J. Stein et al. 43rd IEEE Photovoltaic Specialist Conference. June, 2016.
An Open Source Solar Power Forecasting Tool Using PVLIB Python. W. Holmgren et al. Photovoltaics Specialists Conference. June, 2016. pdf
Evaluation and correction of the impact of spectral variation of irradiance on PV performance. M. Mikofski et al., 43rd IEEE Photovoltaic Specialist Conference, 2016. DOI: 10.1109/PVSC.2016.7749837
Use of Measured Aerosol Optical Depth and Precipitable Water to Model Clear Sky Irradiance. M. Mikofski et al., 44th IEEE Photovoltaic Specialist Conference, 2017. DOI: 10.1109/PVSC.2017.8366314

Irradiance forecasts based on an irradiance monitoring network, cloud motion, and spatial averaging. A. Lorenzo et al. Solar Energy, 122, 1158 (2015). doi: 10.1016/j.solener.2015.10.038
PVLIB Python 2015 PVSC 2015 poster by Holmgren, Lorenzo, Andrews, and Stein. See GitHub repository here.
The University of Arizona Renewable Energy Network uses pvlib-python to model utility and rooftop solar for the Southwest Variable Energy Resource Initiative. For more on this project, please see sveri.energy.arizona.edu or our public report
"Photovoltaic System Fault Detection and Diagnostics using Laterally Primed Adaptive Resonance Theory Neural Network" PVSC 2015 paper/poster by Jones, Stein, Gonzalez, King.

Introduction to the Open Source PV LIB for Python Photovoltaic System Modelling Package. R. Andrews et al. 40th IEEE Photovoltaic Specialist Conference. June, 2014.