Hybrid GA–PSO for optimal placement of static VAR compensators in power system

Abdelmalek Gacem () and Djilani Benattous
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Abdelmalek Gacem: University Med Khaider
Djilani Benattous: University Med Khaider

International Journal of System Assurance Engineering and Management, 2017, vol. 8, issue 1, No 25, 247-254

Abstract: Abstract In recent years, genetic algorithm (GA), particle swarm optimization (PSO) and hybrid genetic algorithm particle swarm optimization (HGAPSO) have attracted considerable attention among various modern heuristic optimization techniques. In this study the HGAPSO, PSO and GA optimization techniques are used for to search the optimal placement and sizing of static VAR compensator (SVC) in power system. The objective function is defined for reducing power loss, voltage deviation and investment costs of SVC. The effectiveness of the proposed hybrid based approach is applied and demonstrated on IEEE 30 Bus network. The results show that the proposed hybrid HGAPSO compared with PSO and GA optimization for performs and giving better solution.

Keywords: FACTS; SVC; HGAPSO; PSO; GA; Multi-objective (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (4)

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DOI: 10.1007/s13198-015-0347-5

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