BFA optimization for voltage and frequency control of a stand-alone wind generation unit

Abstract

A developed control strategy for autonomous wind generation unit is presented. Optimization techniques based on bacteria foraging algorithm and genetic algorithms are used to tune the proposed control parameters. The proposed system mainly consists of induction generator driven by wind turbine, synchronous machine, consumer load, discrete dump load, and gate turn-off thyristor-based power electronics converter. Two control loops are used in this study; the first is to regulate the load bus voltage based on the excitation control of the synchronous machine. The second one simultaneously controls the dump load to absorb excessive power generation, and in turn, regulates the frequency of the proposed power system. The proposed system is tested for turbulent change in wind speed and step change in consumer load. The complete system is modeled and simulated using MATLAB/SIMULINK software package. The performance of the optimized control system is compared with the conventional PID control system. The simulation results show that the optimized control system has good performance as less settling time and less overshoot compared with the case of conventional PID controller.