Visualising risk in generating capacity adequacy studies using clustering and prototypes

Simon H. Tindemans, Goran Strbac

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

1 Citation (Scopus)

Abstract

Generating capacity adequacy studies play a significant role in long term capacity planning. Risks of capacity deficits are usually reported in the form of one or more average quantities, which cannot fully convey the nature of the risks being faced. Chronological Monte Carlo simulations may be used to construct comprehensive multi-dimensional risk profiles, but such profiles tend to be difficult to interpret. This paper proposes the use of a clustering method to partition the risk profile into clusters of similar outcomes with associated probabilities. The results are presented in accessible tabular form, and prototypical scenarios can be analysed in detail to provide further insight.

Original languageEnglish
Title of host publication2015 IEEE Power and Energy Society General Meeting, PESGM 2015
Place of PublicationPiscataway, NJ
PublisherIEEE
Pages1-5
Number of pages5
Volume2015-September
ISBN (Electronic)978-1-4673-8040-9
DOIs
Publication statusPublished - 30 Sep 2015
Externally publishedYes
EventIEEE Power and Energy Society General Meeting, PESGM 2015 - Denver, United States
Duration: 26 Jul 201530 Jul 2015

Conference

ConferenceIEEE Power and Energy Society General Meeting, PESGM 2015
CountryUnited States
CityDenver
Period26/07/1530/07/15

Keywords

  • clustering methods
  • generating capacity adequacy
  • Monte Carlo simulations
  • risk measures

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