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 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…

• AU
  Aristotle University of Thessaloniki