Hybrid CSA-GWO Algorithm-Based Optimal Control Strategy for Efficient Operation of Variable-Speed Wind Generators

Abstract

The hybridization of two algorithms is recently emerging to find superior solutions to the optimization problems. This paper exhibits a new hybrid cuckoo search algorithm and grey wolf optimizer (CSA-GWO)-based on control scheme to enhance the transient stability of the grid-tied variable-speed wind energy conversion system. The variable-speed wind turbine (VSWT) direct drive permanent-magnet synchronous generator, which is interlinked to the network through a full-scale converter. The generator- and grid-side converters are controlled by using an optimum proportional-integral (PI) controller. Each vector control scheme for the generator/grid-side converters has four CSA-GWO-based PI controller. In this study, the integral squared error criterion is used as an objective function. The CSA-GWO-based PI controller efficacy is validated by comparing its results with that obtained by using the genetic algorithm (GA)-based PI controller. The performance of the proposed control scheme is checked during various fault conditions. The control scheme quality is legalized by the simulation results that are achieved using MATLAB/Simulink program. With the CSA-GWO based PI controller, the dynamic and transient stability of grid-connected wind generator systems can be enhanced.