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Application of artificial intelligence algorithms in solving power system state estimation problem.

M. Tech. Electrical Engineering. / Discusses the practical management of electrical networks, no perfect monitoring of an electrical power system state is available, either because it is expensive or technically unfeasible due to the poor quality of the available measurements in the control centre. To have a stable network, the control centre must receive the network information to be able to provide a proper security in unforeseen situation. As a power system network is a complex and a non-linear system, it is important to use more advanced methods for its analysis and control in a real time environment. The aim of this research work is therefore, to apply several state estimation algorithms using artificial intelligence by developing their mathematical models for the purpose of comparing their performances in estimating the state variable of the power system. The three types of state estimation algorithms investigated for this research work are: the Particle Swarm Optimisation (PSO), the Genetic Algorithm (GA) and the Newton method for state estimation (NSE).

Identiferoai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:tut/oai:encore.tut.ac.za:d1001381
Date January 2013
CreatorsTungadio,Diambomba Hyacinthe-St,
Source SetsSouth African National ETD Portal
LanguageEnglish
Detected LanguageEnglish
TypeText
FormatPDF

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