Abstract:
Wind power generation systems, which can be run at constant speed or variable speed, are
gaining a lot of attention as clean and secure renewable energy sources. Due to an increase
in the production of wind energy, variable speed generation systems are more appealing than
fixed speed systems. A variable speed wind turbine should run as close as practical to its ideal
power coefficient to maximize the harvest of wind energy. Here, the speed of wind turbine with
dual mass is controlled using a Fractional Order PID (FOPID) controller whose parameters
are tuned using computational intelligence approaches like Particle Swarm Optimization (PSO)
and Genetic Algorithm (GA). A comparison with the two computational tuning approaches is
carried out in different wind profiles using MATLAB software. Simulation results shows the
higher performance of FOPID controller design technique when compared with conventional
PID in terms of multiple performance evaluation indices
