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Baseline and target values for PV forecasts: Toward improved solar power forecasting

  • Jie Zhang
  • , Bri Mathias Hodge
  • , Joseph Simmons
  • , Siyuan Lu
  • , Hendrik F. Hamann
  • , Edwin Campos
  • , Brad Lehman
  • , Venkat Banunarayanan
  • National Renewable Energy Laboratory
  • University of Arizona
  • IBM
  • Argonne National Laboratory
  • Northeastern University
  • United States Department of Energy

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Scopus citations

Abstract

Accurate solar power forecasting allows utilities to get the most out of the solar resources on their systems. To truly measure the improvements that any new solar forecasting methods can provide, it is important to first develop (or determine) baseline and target solar forecasting at different spatial and temporal scales. This paper aims to develop baseline and target values for solar forecasting metrics. These were informed by close collaboration with utility and independent system operator partners. The baseline values are established based on state-of-the-art numerical weather prediction models and persistence models. The target values are determined based on the reduction in the amount of reserves that must be held to accommodate the uncertainty of solar power output.

Original languageEnglish
Title of host publication2015 IEEE Power and Energy Society General Meeting, PESGM 2015
PublisherIEEE Computer Society
ISBN (Electronic)9781467380409
DOIs
StatePublished - Sep 30 2015
EventIEEE Power and Energy Society General Meeting, PESGM 2015 - Denver, United States
Duration: Jul 26 2015Jul 30 2015

Publication series

NameIEEE Power and Energy Society General Meeting
Volume2015-September
ISSN (Print)1944-9925
ISSN (Electronic)1944-9933

Conference

ConferenceIEEE Power and Energy Society General Meeting, PESGM 2015
Country/TerritoryUnited States
CityDenver
Period07/26/1507/30/15

Keywords

  • grid integration
  • numerical weather prediction
  • operating reserve
  • ramp forecasting
  • solar power forecasting

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