SVC Parameters Optimization Using a Novel Integrated MCDM Approach

Nowadays, multi-criteria decision-making (MCDM) methods are used widely in many fields of research and applications. Many studies have shown that MCDM approaches effective determining the optimal solution to a variety symmetrical asymmetrical problems with numerous parameters. This article investigates novel approach using multi criteria decision making optimize parameters static var compensator (SVC) power system stabilizers (PSS). The proposed technique integrates similarity membership function reduction algorithm (SMFRA), removal effects (REC) combined compromise (CoCoSo). In first stage, (SMFRA) is employed select most dominant controller optimization process. Secondly, weights reduced computed based on (REC). Finally, (CoCoSo) method searches for setting A detailed sensitivity analysis presented evaluate obtained results. It found suggested integrated time saving, easily implemented low computation burden, which can successfully be solve wide range issues, both comparable dissimilar.