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

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