Review and Comparison of Genetic Algorithm and Particle Swarm Optimization in the Optimal Power Flow Problem

Georgios Papazoglou and Pandelis Biskas ()
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Georgios Papazoglou: School of Electrical and Computer Engineering, Aristotle University of Thessaloniki, 541 24 Thessaloniki, Greece
Pandelis Biskas: School of Electrical and Computer Engineering, Aristotle University of Thessaloniki, 541 24 Thessaloniki, Greece

Energies, 2023, vol. 16, issue 3, 1-25

Abstract: Metaheuristic optimization techniques have successfully been used to solve the Optimal Power Flow (OPF) problem, addressing the shortcomings of mathematical optimization techniques. Two of the most popular metaheuristics are the Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). The literature surrounding GA and PSO OPF is vast and not adequately organized. This work filled this gap by reviewing the most prominent works and analyzing the different traits of GA OPF works along seven axes, and of PSO OPF along four axes. Subsequently, cross-comparison between GA and PSO OPF works was undertaken, using the reported results of the reviewed works that use the IEEE 30-bus network to assess the performance and accuracy of each method. Where possible, the practices used in GA and PSO OPF were compared with literature suggestions from other domains. The cross-comparison aimed to act as a first step towards the standardization of GA and PSO OPF, as it can be used to draw preliminary conclusions regarding the tuning of hyper-parameters of GA and PSO OPF. The analysis of the cross-comparison results indicated that works using both GA and PSO OPF offer remarkable accuracy (with GA OPF having a slight edge) and that PSO OPF involves less computational burden.

Keywords: Optimal Power Flow; Genetic Algorithm; Particle Swarm Optimization; hyper-parameter tuning; metaheuristic optimization (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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