A novel unified maximum power extraction framework for PMSG based WECS using chaotic particle swarm optimization derivatives

Abstract

The most important issue in the use of wind energy conversion systems (WECS) is to ensure maximum power extraction for attaining increased efficiency. In this study, maximum power extraction frameworks operating the state-of-the-art optimization methods are presented for permanent magnet synchronous generator (PMSG) based WECS. These frameworks consist of a fast terminal sliding mode control (FTSMC) based MPPT controller and a hybrid MPPT approach that combines chaotic based particle swarm optimization (PSO) derivatives and optimal relation based (ORB) method. Chaotic dynamic weight PSO (CDW-PSO) and Gauss map based chaotic PSO (GM-CPSO), which are remarkable and recent optimization techniques, are utilized to achieve optimum coefficients to ensure efficient MPPT operation. After acquiring the optimum coefficients, the framework passes to ORB operation part. Moreover, the proposed frameworks track extracted power within certain limits during the operation of WECS and make transition between the best coefficients if necessary. On the other hand, FTSMC is used to track the MPPT references that are determined via hybrid MPPT algorithms. To validate the proposed frameworks, they are tested in Matlab/Simulink environment for three specific wind speed scenarios. GM-CPSO based ORB and CDW-PSO based ORB MPPT methods are compared with ORB and tip speed ratio (TSR) methods under these scenarios. Consequently, it is revealed that proposed methods contribute to MPPT efficiency by providing higher power extraction than other conventional methods.