Cluster Identification for Optimal Placement of Static Var Compensator

Author

Jumaat, S.A. ; Musirin, I. ; Othman, M.M. ; Mokhlis, H.

Author_Institution

Fac. of Electr. & Electron. Eng., Univ. Tun Hussein Onn Malaysia, Parit Raja, Malaysia

fYear

2013

fDate

3-4 June 2013

Firstpage

546

Lastpage

551

Abstract

This paper introduces a new concept of artificial intelligence based algorithm for clustering the placement of SVCs in power system. The algorithm is based on particle swarm optimization (PSO) technique with objective function to minimize the transmission loss in the system. Experiments were performed on the IEEE 30- and IEEE 118-bus RTS to realize the effectiveness of the proposed technique, while verification was conducted through comparative studies with evolutionary programming (EP).

Keywords

artificial intelligence; evolutionary computation; particle swarm optimisation; power engineering computing; power transmission; static VAr compensators; IEEE 118-bus RTS; IEEE 30-bus RTS; PSO; artificial intelligence; cluster identification; evolutionary programming; optimal placement; particle swarm optimization; power system; static var compensator; transmission loss; Conferences; Load management; Optimization; Power engineering; Power system stability; Propagation losses; Static VAr compensators;

fLanguage

English

Publisher

ieee

Conference_Titel

Power Engineering and Optimization Conference (PEOCO), 2013 IEEE 7th International

Conference_Location

Langkawi

Print_ISBN

978-1-4673-5072-3

Type

conf

DOI

10.1109/PEOCO.2013.6564608

Filename

6564608