Novel Nonlinear PI Controller Using Metaheuristic Algorithms for Speed Control of Wind Turbine Systems

Abstract

Wind turbines operate under highly dynamic conditions influenced by unpredictable wind profiles and external disturbances. The nonlinear characteristics of their dynamic models further complicate their modeling and control. This research focuses on optimizing the power output of a Wind Energy Conversion System (WECS) equipped with a Permanent Magnet Synchronous Generator (PMSG). To achieve this, a Maximum Power Point Tracking (MPPT) strategy is developed, integrating an innovative nonlinear PI controller. The parameters of this controller are fine-tuned using advanced meta-heuristic optimization techniques, including Particle Swarm Optimization (PSO), Harris Hawks Optimization (HHO), and Golden Jackal Optimization (GJO). Simulation results highlight the superior performance of the GJO-NLPI controller, demonstrating exceptional accuracy and rapid response in regulating mechanical rotation speed, while effectively reducing overshoot. The proposed control architecture showcases significant advancements in power extraction efficiency and dynamic performance.