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

19 Scopus citations

Abstract

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.
Pages972-975
Number of pages4
ISBN (Electronic)9781509027248
DOIs
StatePublished - Nov 18 2016
Externally publishedYes
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
Volume2016-November
ISSN (Print)0160-8371

Other

Other43rd IEEE Photovoltaic Specialists Conference, PVSC 2016
Country/TerritoryUnited States
CityPortland
Period6/5/166/10/16

Keywords

  • forecasting
  • performance modeling
  • PV modeling
  • software

ASJC Scopus subject areas

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

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