Abstract

In this study, proportional valve-controlled semi-rotary electrohydraulic actuator proposed for horizontal axis wind turbine pitch movement. Semi-rotary actuator can be connected directly to the wind turbine blade, which reduces mechanical complexity compare to linear electrohydraulic actuator system. Adaptive torque control scheme has been adopted for the horizontal axis wind turbine in region II; however, adaptive pitch control has been adopted for region III. Optimum pitch demand and torque demand have been estimated through blade element momentum theory based on predicted wind speed. The control objective is to track maximum power through torque control in region II and to maintain rated power with structural safety by limiting thrust force in the region III. The proposed wind turbine model has been validated with 1.5-MW wind turbine experimental data. Feedforward fractional-order proportional–integral–derivative controller with adaptive teaching–learning based optimization algorithm has been developed for wind turbine control application. In region II, feedforward control signal generates due to torque demand and feedback control signal generates due to combined torque and pitch error. However, in region III, feedforward and feedback control estimated with pitch demand and combined pitch and torque error, respectively. The proposed controller performance has been tested with sinusoidal, step and actual wind data. The controller performance also compared with respect to other conventional controllers. Performance of the adaptive teaching–learning-based optimization has been compared with genetic algorithm and teaching–learning-based optimization process. Sensitivity analysis has been performed with proposed controller to check the effectiveness of the optimization. Furthermore, the proposed controller response has been compared with existing data of 1.5-MW wind turbine. Lyapunov-based stability analysis has been performed to ensure stability and convergence of the proposed system. Proposed controller performance has been found better compare to the existing result.

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call