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

1 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 publication2017 IEEE 44th Photovoltaic Specialist Conference, PVSC 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1777-1780
Number of pages4
ISBN (Electronic)9781509056057
DOIs
StatePublished - 2017
Externally publishedYes
Event44th IEEE Photovoltaic Specialist Conference, PVSC 2017 - Washington, United States
Duration: Jun 25 2017Jun 30 2017

Publication series

Name2017 IEEE 44th Photovoltaic Specialist Conference, PVSC 2017

Other

Other44th IEEE Photovoltaic Specialist Conference, PVSC 2017
Country/TerritoryUnited States
CityWashington
Period6/25/176/30/17

Keywords

  • Forecasting
  • Performance modeling
  • PV modeling
  • Software

ASJC Scopus subject areas

  • Renewable Energy, Sustainability and the Environment
  • Electrical and Electronic Engineering
  • Electronic, Optical and Magnetic Materials

Fingerprint

Dive into the research topics of 'An open source solar power forecasting tool using PVLIB-Python'. Together they form a unique fingerprint.

Cite this