An implicit switching model for distribution network reliability assessment

Yang Yang, Simon Tindemans, Goran Strbac

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

Abstract

Modern active distribution networks make use of intelligent switching actions to restore supply to end users after faults. This complicates the reliability analysis of such networks, as the number of possible switching actions grows exponentially with network size. This paper proposes an approximate reliability analysis method where switching actions are modelled implicitly. It can be used graphically as a model reduction method, and simulated using time-sequential or state sampling Monte Carlo methods. The method is illustrated on a simple distribution network, and reliability indices are reported both as averages and distributions. Large speedups result from the use of biased non-sequential Monte Carlo sampling - a method that is hard to combine with explicit switching models.

Original languageEnglish
Title of host publication19th Power Systems Computation Conference, PSCC 2016
Place of PublicationPiscataway, NJ
PublisherIEEE
Pages1-7
Number of pages7
ISBN (Electronic)978-88-941051-2-4
DOIs
Publication statusPublished - 10 Aug 2016
Externally publishedYes
Event19th Power Systems Computation Conference, PSCC 2016 - Genova, Italy
Duration: 20 Jun 201624 Jun 2016

Conference

Conference19th Power Systems Computation Conference, PSCC 2016
CountryItaly
CityGenova
Period20/06/1624/06/16

Keywords

  • distribution networks
  • Monte Carlo simulations
  • network topology
  • reliability analysis

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