Artificial Intelligence application to Malaysian electrical powersystem

Ahmed M A Haidar, Azah Mohamed, Aini Hussain, Norazila Jaalam

Research output: Contribution to journalArticle

7 Citations (Scopus)

Abstract

Vulnerability assessment and control of a power system is important to power utilities due to the blackouts in recent years in many countries which indicate that power systems today are vulnerable when exposed to unforeseen catastrophic contingencies. A fast and accurate technique to assess the level of system strength or weakness is some of the essential requirements for maintaining security of modern power systems, particularly in competitive energy markets. This paper presents intelligent artificial techniques for vulnerability assessment of Malaysian power system and recommends preventive control measures. Accurate techniques for vulnerability assessment and control of power systems are developed. In vulnerability assessment, power system loss index is used as a vulnerability parameter, neural network weight extraction is employed as the feature extraction method and the generalized regression neural network is used to predict vulnerability of a power system. As for vulnerability control, load shedding is considered by using the neuro-fuzzy technique. Finally, the paper presents and discusses the results from this research with recommendations.

Original languageEnglish
Pages (from-to)5023-5031
Number of pages9
JournalExpert Systems with Applications
Volume37
Issue number7
DOIs
Publication statusPublished - Jul 2010

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Artificial intelligence
Neural networks
Feature extraction

Keywords

  • Fuzzy controller
  • Neural network
  • Power system loss
  • Vulnerability assessment

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Engineering(all)

Cite this

Artificial Intelligence application to Malaysian electrical powersystem. / Haidar, Ahmed M A; Mohamed, Azah; Hussain, Aini; Jaalam, Norazila.

In: Expert Systems with Applications, Vol. 37, No. 7, 07.2010, p. 5023-5031.

Research output: Contribution to journalArticle

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