An open source solar power forecasting tool using PVLIB-Python

William F. Holmgren, Derek G. Groenendyk

Research output: Chapter in Book/Report/Conference proceedingConference contribution

24 Scopus citations


We describe an open-source PV power forecasting tool based on the PVLIB-Python library. The tool allows users to easily retrieve standardized weather forecast data relevant to PV power modeling from NOAA/NCEP/NWS 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. Standardized, open source, reference implementations of forecast methods using publicly available data may help advance the state-of-the-art of solar power forecasting.

Original languageEnglish (US)
Title of host publication2016 IEEE 43rd Photovoltaic Specialists Conference, PVSC 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages4
ISBN (Electronic)9781509027248
StatePublished - Nov 18 2016
Event43rd IEEE Photovoltaic Specialists Conference, PVSC 2016 - Portland, United States
Duration: Jun 5 2016Jun 10 2016

Publication series

NameConference Record of the IEEE Photovoltaic Specialists Conference
ISSN (Print)0160-8371


Other43rd IEEE Photovoltaic Specialists Conference, PVSC 2016
Country/TerritoryUnited States


  • PV modeling
  • forecasting
  • performance modeling
  • software

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Industrial and Manufacturing Engineering
  • Electrical and Electronic Engineering

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