A Comparison of PV Power Forecasts Using PVLib-Python

We used the open-source PVLib-Python library to create PV power forecasts for a fleet of utility scale power plants and assessed their accuracies. PVLib-Python allows users to easily retrieve standardized weather forecast data relevant to PV power modeling from NOAA models including the GFS, NAM, RAP, HRRR, and the NDFD. A PV power forecast can then be obtained using the weather data as inputs to the comprehensive modeling capabilities of PVLib-Python. We used these models to benchmark the performance of the University of Arizona's configuration of the Weather Research and Forecasting model. Standardized, open source, reference implementations of forecast methods using publicly available data may help advance the state-of-the-art of solar power forecasting.