Optimal siting and sizing of unified power flow controller using covariance matrix adapted evolution strategy in grid integrated wind energy conversion systems

Abstract

This paper discusses the application of covariance matrix adapted evolution strategy (CMAES) algorithm on wind energy conversion systems. CMAES is a class of continuous evolutionary algorithm that generates new population members by sampling from a probability distribution that is constructed during the optimization process. Modified IEEE 14 bus system is considered for simulation purpose. The critical evaluation of maximum loadability of the system is determined. Statistical performance of CMAES algorithm reveals that the best value of maximum loadability is obtained when compared to primal dual interior point method. Even though CMAES takes higher computation time, this method gives the best loadability margin.