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Comparing resource adequacy metrics and their influence on capacity value

  • National Renewable Energy Laboratory

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

25 Citations (Scopus)

Abstract

Traditional probabilistic methods have been used to evaluate resource adequacy. The increasing presence of variable renewable generation in power systems presents a challenge to these methods because, unlike thermal units, variable renewable generation levels change over time because they are driven by meteorological events. Thus, capacity value calculations for these resources are often performed to simple rules of thumb. This paper follows the recommendations of the North American Electric Reliability Corporation's Integration of Variable Generation Task Force to include variable generation in the calculation of resource adequacy and compares different reliability metrics. Examples are provided using the Western Interconnection footprint under different variable generation penetrations.

Original languageEnglish
Title of host publication2014 International Conference on Probabilistic Methods Applied to Power Systems, PMAPS 2014 - Conference Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781479935611
DOIs
Publication statusPublished - 17 Nov 2014
Externally publishedYes
Event2014 International Conference on Probabilistic Methods Applied to Power Systems, PMAPS 2014 - Durham, United Kingdom
Duration: 7 Jul 201410 Jul 2014

Publication series

Name2014 International Conference on Probabilistic Methods Applied to Power Systems, PMAPS 2014 - Conference Proceedings

Conference

Conference2014 International Conference on Probabilistic Methods Applied to Power Systems, PMAPS 2014
Country/TerritoryUnited Kingdom
CityDurham
Period7/07/1410/07/14

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy

Keywords

  • Capacity planning
  • power system reliability
  • probability
  • solar energy
  • wind energy

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