Adaptive Genetic Algorithm Based Parameters Optimization of PI Controller for Battery System in Wind Farm

Abstract

The randomness and intermittence of wind farm real power generation bring challenges to power system operation, and installing battery system for the mitigation of the fluctuation of wind farm output, following the short-term forecasting curve, even adjusting the output according to the operator’s requirement is a possible way to address the problem from the wind farm side. After a review of various storage control strategies for stabilizing the fluctuation of wind power output, the model of battery energy storage system as well as its control strategy is introduced. Adaptive Genetic Algorithm (AGA) is used for the optimization of PI control parameters. Simulation shows the effectiveness of the proposed method. Moreover, comparing with the trial-and-error method, the optimization algorithm proposed has the advantage of finding the optimal parameters under the lack of experience on PID control, and combined with trial-and-error method, the difficulties engineer could face on tuning the parameters of PI controller is decreased, which increases the feasibility for parameters of PI controller’s being transplanted to similar applications.