Optimization of Electrical Power Systems Using Hybrid PSO-GA Computational Algorithm: a Review

Abstract

Since the intelligent optimization algorithms has been successful in solving tested functions, the electrical power system researchers have done many studies and applications using optimal strategies. Any topic of power system has been optimized using those algorithms such as the quality, the stability, the voltage profile, the reliability, the smart grid, and the economic generations. With the increasing demand for electricity, the traditional methods to solve the optimization problems cannot meet the demand, and with the deepening of research, many emerging technologies are applied to the solution of power system optimization problems. However, when solving practical engineering problems, there are still many challenges. Genetic Algorithm and Particle Swarm Optimization are two of the most famous strategies that are applied to solve the power system problems. This paper focuses on the advantages of advance hybrid computational algorithm in order to optimize the performance of electrical power system. The detail of the hybrid of classical intelligent algorithm Genetic Algorithm (GA) and Particle Swarm Optimization (PSO), which have been used to solve the power system problems, has been briefly summarized. In addition, the hybrid algorithm is classified into several types depending on the method of the computation between them. The parallel, the Serial, and the impeded hybrid are the main types of this classification. Finally, future suggestions of the important power system applications using the hybrid GA-PSO are introduced according to the corresponding methods, which have given good results for engineering systems.