Optimized PI Controller Tuning for reactive power control of Stand-Alone DFIG Wind Energy Systems Utilizing Grey Wolf Optimization with Simplex Algorithm

Abstract

Wind energy is an essential element of the global shift towards renewable energy, providing clean and sustainable electricity generation. The Doubly Fed Induction Generator (DFIG) is extensively utilized in variable-speed wind turbine systems owing to its efficiency and controllability. This research introduces a comprehensive control approach for a stand-alone Doubly Fed Induction Generator (DFIG) utilizing a Proportional-Integral (PI) controller optimized via the integration of Grey Wolf Optimization and the Simplex algorithm (GWO-SM). A laboratory prototype has been created, including a Brushless DC (BLDC) motor that simulates wind fluctuations and a wound rotor induction machine operating as the Doubly Fed Induction Generator (DFIG). System identification techniques are utilized to describe the reactive power and speed control loops using input-output data. The new GWO-SM method is evaluated against traditional Grey Wolf Optimization (GWO) and Particle Swarm Optimization (PSO) across several test settings, including abrupt alterations in speed and load. The results indicate that GWO-SM surpasses both PSO and GWO by attaining quicker transient responses, reduced steady-state error, and enhanced resilience. The results confirm the efficacy of GWO-SM as a superior tuning technique for PI controllers in independent wind energy applications.

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