A Review of Particle Swarm Optimization and its Applications in Wind Energy System

Abstract

This paper uses particle swarm optimization (PSO) to achieve optimal wind synchronization power generation scheduling. PSO is an evolutionary highly efficient and has proven to be an effective, robust, and simple optimization algorithm. Different methods were used to understand how this algorithm operates and to try to develop its convergence properties for different kinds of issues. Such methods proceed through numerical testing, from heuristic to mathematical analysis. In this article, we analyze the efficiency of the PSO approach in dealing with wind energy system problems. The main feature in the analysis is the generating power, and the design variables are some technological restrictions imposed in order to assess the highest proportion of wind generator energy that can be implemented into the system. Wind power production can fluctuate, either hourly or daily. The stand-alone unit must therefore have some means of storing energy, which can be used to supply the load later during periods of low or no power consumption. This technique will be useful in determining the effective energy management strategy to meet the necessary load demand at minimum operating cost while meeting device equity and inequality constraints.