Title :
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
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;
Conference_Titel :
Power Engineering and Optimization Conference (PEOCO), 2013 IEEE 7th International
Conference_Location :
Langkawi
Print_ISBN :
978-1-4673-5072-3
DOI :
10.1109/PEOCO.2013.6564608
