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Journal of Energy : Energija, Vol. 60 No. 1-4, 2011.

Original scientific paper

Application of ANN and Genetic Algorithm for Evaluation the Optimum Location of Arresters on Power Networks due to the Switching Overvoltages

Reza Shariatinasab ; Amirkabir University of Technology Iran
Behrooz Vahidi ; Amirkabir University of Technology Iran
Seyed Hossein Hosseinian ; Amirkabir University of Technology Iran
Akihiro Ametani ; Doshisha University Japan

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Abstract

Switching surges are of primary importance in insulation co-ordination of EHV lines, as well as in
designing insulation of apparatuses. The magnitude and shape of the switching overvoltages vary with
the system parameters, network configuration and the point-on-wave where the switching operation
takes place. This paper presents an artificial neural network (ANN) based approach to estimate the
peak value of overvoltages and the global risk of failure generated by switching transients during line
energizing or re-energizing in different nodes of a power network. Then a genetic algorithm (GA)
based method is developed to find the best position of surge arresters on power networks so as to
minimize the global risk of the network.

Keywords

Switching surges - Artificial neural network (ANN) - Genetic algorithm (GA) - Surge arrester - Risk analysis - EMTP/ATP Draw

Hrčak ID:

198493

URI

https://hrcak.srce.hr/198493

Publication date:

20.6.2017.

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