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A Review on PSO Models in Power System Operation

Optimization is one of the most important aspects in power system study fields, especially in power system operation, and a verity of models and approaches has been presented in this area. Each model tries to get the best solution as an optimal point, without trapping in local optima. As a powerful tool, modeling based on expert systems and simulation of natural process has an importance and noticeable value in this regard. Since most of power system optimization problems are complex and nonlinear with heavy equality and inequality constraints, the heuristic optimization techniques such as Particle Swarm Optimization (PSO) are considered as realistic and powerful solution schemes to obtain the optimal or quasi-optimal solutions in power system optimization problems. As a lot of papers and researches have been published based on applying PSO in power system operation studies, in this paper a general view on PSO proposed models and approaches in this related is presented. The studies such as UC, ED, OPF, Reactive power compensation, Load forecasting, FACTS, and so on based on PSO proposed models, comparing their benefits and drawbacks are presented. Keywords—Particle Swarm Optimization (PSO), Power