Wind Turbine Pitch System Control Through Modified Real Coded Genetic Algorithm Fractional Order Controller

Wind energy gradually becomes a best alternative solution for power generation instead of fossil fuels with increasing installation capacity. Wind turbines experience fatigue loads in large scale with increasing size of wind turbine and these fatigue loads are highly variable with variation of wind speed. These loads impact severely on fatigue life of wind turbine components like rotor blades, in above rated wind speed condition. The fatigue life of wind turbine can be increased in above rated wind speed with pitch control of rotor blades, it helps to mitigate forces and enhances power quality generation. The objective function in present work is minimization of pitch error with proper selection of pitch actuating system and controller. Electrohydraulic pitch actuating systems become very popular over electromechanical systems due to its capability of generating higher forces with small size components and capability of withstanding external loads continuously irrespective of disturbance outside of the system. Feedforward fractional order PID controller is proposed for desire pitch of rotor blade. The control variables of feedforward fractional order PID controller were optimized by using advanced adaptive real coded genetic algorithm. Various wind profiles have been considered for investigating the performance of 1.5 MW wind turbine. The proposed algorithm has shown better performance compare to existing real coded genetic algorithm in terms of minimizing pitch error of rotor blade. Highlights