Design Controller Blade Pitch Angle Wind Turbine Using Hybrid Differential Evolution Algorithm-Particle Swarm Optimization

Abstract

This paper investigates the application of blade pitch angle controller to stabilize the frequency and protection again disaster of wind turbine power system. The blade pitch angle controller optimized by one of the metaheuristic algorithm called Hybrid Differential Evolution Algorithm-Particle Swarm Optimization (HDEAPSO). HDEAPSO is a hybrid algorithm between Differential Evolution Algorithm and Particle Swarm Optimization. To investigate and design the application of blade pitch angle can be done by performing the simulation using MATLAB. Simulation if performed by comparing the stability response of frequency and pitch angle at the wind turbine using conventional controller, optimized by PSO and using Hybrid Differential Evolution Algorithm-Particle Swarm Optimization (HDEAPSO). The simulation result represent that by optimizing blade pitch angle controller using Hybrid Differential Evolution-Particle Swarm Optimization can damp the frequency of wind turbine from −0.01363 pu to −0.1304 pu and reduce settling time from 46.86 second to 33.48 second when there are wind with speed 2 m/s.