Enhanced Performance of Multi-Turbine Systems Through Hybrid Controller Optimization

Abstract

Maintaining high energy quality and power stability remains a key challenge in modern wind energy systems due to nonlinear dynamics, operational uncertainties, and generator disturbances. To address these issues, this paper presents a hybrid control approach that combines fractional-order control, a feedback proportional–integral (FPI) regulator, and a genetic algorithm–based optimization scheme. The designed regulator is designed to suppress energy oscillations and overcome the energy quality limitations associated with traditional direct power control and PI-based control methods. Fractional-order control enhances dynamic flexibility and robustness, while the genetic algorithm ensures optimal tuning of controller parameters under varying operating conditions. The effectiveness of the designed method is evaluated on a 1500 kW doubly-fed induction generator–based multi-rotor wind power system using MATLAB simulations. Comparative results demonstrate notable improvements in power stability, energy quality, and overall system performance across diverse scenarios, confirming the suitability of the proposed approach for advanced renewable energy applications.