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2021 | OriginalPaper | Buchkapitel

Choice of Selection Methods in Genetic Algorithms for Power System State Estimation

verfasst von : Thanh-Son Tran, Thi-Thanh-Hoa Kieu

Erschienen in: Advances in Engineering Research and Application

Verlag: Springer International Publishing

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Abstract

The state estimator plays an important role in power system operation. It is used to monitor state parameters, thereby it helps the operators make control decisions when the parameters exceed the permissible limits to ensure the system operate in a normal and secure state. To solve this problem, we can use artificial intelligence methods such as genetic algorithms. The genetic algorithms consist of three main operators: selection, crossover, and mutation. Among them, the selection of individual parents plays an essential role as it affects the performance of the algorithm. This paper studies the effect of selection methods on results of power system state estimation. The results depend significantly on the choice of selection methods and show that the roulette wheel selection is the best choice.

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Titel: Choice of Selection Methods in Genetic Algorithms for Power System State Estimation
verfasst von: Thanh-Son Tran
Thi-Thanh-Hoa Kieu
Verlag: Springer International Publishing
Buch: Advances in Engineering Research and Application
Print ISBN: 978-3-030-64718-6

Electronic ISBN: 978-3-030-64719-3

Copyright-Jahr: 2021
DOI: https://doi.org/10.1007/978-3-030-64719-3_26

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