Symbiotic organisms search algorithm‐based optimal control strategy for efficient operation of variable‐speed wind generators

Abstract

The penetration rate of grid-tied wind turbine generator systems (WTGSs) into the existing electricity networks is rapidly increasing worldwide. Huge efforts are exerted for improving the characteristics of variable-speed wind energy conversion systems. This study exhibits a novel symbiotic organisms search algorithm (SOSA)-based optimal control strategy for achieving efficient operation of a grid-connected WTGS. The optimal control strategy relies on proportional–integral (PI) controllers, which are properly fine-tuned using the SOSA. The simulation-based optimisation method is considered in the optimisation process, where the integration of the square error criterion is selected as a fitness function. To obtain realistic performances, practical wind speed data extracted from the Zaafarana power plant in Egypt are used in the analyses. The efficacy of the SOSA-based optimal PI control strategy is compared with that realized using the grey wolf optimiser algorithm (GWOA)-based PI control scheme, considering network disturbances. The feasibility of the proposed control strategy is validated using the simulation studies, which are implemented using MATLAB/Simulink software. Notably, the proposed SOSA-based optimal control strategy is considered to be a precise means of improving the behaviour of grid-tied WTGSs.