Artificial intelligence application to Malaysian electrical powersystem
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.
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