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

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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.

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Correspondence to Abdelmalek Gacem.

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Gacem, A., Benattous, D. Hybrid GA–PSO for optimal placement of static VAR compensators in power system. Int J Syst Assur Eng Manag 8 (Suppl 1), 247–254 (2017). https://doi.org/10.1007/s13198-015-0347-5

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  • DOI: https://doi.org/10.1007/s13198-015-0347-5

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