A review of artificial intelligence techniques as applied to adaptive autoreclosure, with particular reference to deployment with wind generation

Simon Le Blond, Raj Aggarwal

Research output: Chapter or section in a book/report/conference proceedingChapter or section

115 Downloads (Pure)

Abstract

This paper presents a survey of artificial intelligence techniques that have hitherto been applied to adaptive autoreclosure, namely artificial neural networks, fuzzy logic and genetic algorithms. The aim is to discern the most suitable techniques for applying adaptive autoreclosure to systems with high penetrations of wind power. Traditionally, adaptive autoreclosure schemes have been implemented using a combination of signal processing and artificial neural networks. A number of variations on this conventional approach are proposed in this paper. Qualitative discussion shows that in theory, a combination of the examined AI techniques will provide the most robust methodology, combining the strengths of each technique whilst minimizing weaknesses.
Original languageEnglish
Title of host publicationProceedings of the 44th International Universities Power Engineering Conference (UPEC), 2009
PublisherIEEE
Pages855-859
Number of pages5
ISBN (Electronic)978-0-947649-44-9
ISBN (Print)9781424468232
Publication statusPublished - 11 Mar 2010
Event44th International Universities Power Engineering Conference, UPEC2009, September 1, 2009 - September 4, 2009 - Glasgow, UK United Kingdom
Duration: 11 Mar 2010 → …

Publication series

NameProceedings of the Universities Power Engineering Conference
PublisherIEEE Computer Society

Conference

Conference44th International Universities Power Engineering Conference, UPEC2009, September 1, 2009 - September 4, 2009
Country/TerritoryUK United Kingdom
CityGlasgow
Period11/03/10 → …

Fingerprint

Dive into the research topics of 'A review of artificial intelligence techniques as applied to adaptive autoreclosure, with particular reference to deployment with wind generation'. Together they form a unique fingerprint.

Cite this