Differential evolution with Grey Wolf Adapting Optimizer for multi-pid Control Optimizer

In this paper, a novel grey wolf optimizer with differential evolution to optimize the parameters of doubly-fed induction generator with maximum power point tracking strategy.The proposed grey wolf optimizer with differential evolution consists of improved grey wolf optimizer and adaptive differential evolution.The grey wolves of the improved grey wolf optimizer contain four types wolves, i.e., alpha wolves, beta wolves, delta wolves, and omega wolves.The improved grey wolf optimizer can wider and deeper achieve the optimization task.The adaptive differential evolution is applied to cooperate with improved grey wolf optimizer to solve global optimization over continuous spaces.the simulation results on DFIG with MPPT strategies in three real-world cases verify that the GOE accelerated by DFCM can effectively obtain global optimization.The simulation results on doubly-fed induction generator with maximum power point tracking strategy in three cases studies verify that the proposed grey wolf optimizer with differential evolution can effectively obtain the global optimization solution for non-smooth problems.