Performance Analysis of Fractional-Order Controllers for Blade Pitch Angle Control of a Wind Turbine

Designing an optimal blade pitch angle controller for a wind turbine (WT) presents a critical engineering challenge, affecting the turbine's reliability, safety, and power output efficiency. This research investigates the blade pitch angle controller design for a 500 kW WT using five different fractional-order controllers (FOCs) in a simulated environment. To optimize the parameters of these FOCs, a bio-inspired metaheuristic method known as the artificial hummingbird algorithm (AHA) is employed. A fitness function is determined based on the error between nominal output power and measured output power of the WT, and an optimization process is performed to minimize this fitness function. For reliability of the optimization process, 30 independent runs are performed, and their statistical data is recorded. Following the optimization process, the power output and time response characteristics of the WT system are evaluated by simulation studies to determine their performance. The simulation results indicate that the system controlled with the fractional-order proportional-derivative (FOPD) controller achieves the best transient response characteristics with a maximum overshoot of 1.104%, maximum undershoot of 2.491% and settling time of 0.037 seconds and outperforms the other four FOCs.