DC Microgrid Enhancement via Chaos Game Optimization Algorithm

Abstract

Microgrids are increasingly being adopted as alternatives to traditional power transmission networks, necessitating improved performance strategies. Various mathematical optimization techniques are used to determine optimal controller parameters for these systems. These optimization methods can generally be categorized into natural, biological, and engineering-based approaches. In this research, the authors evaluated and compared several optimization techniques to enhance the secondary controller of DC microgrids, focusing on reducing operating time and minimizing error rates. Optimization tools were utilized to identify the optimal gain control parameters, aiming to achieve the best possible system performance. The enhanced controller response enables quicker recovery to steady-state conditions during sudden disturbances. The root-mean-square error (RMSE) served as a performance metric, with the proposed approach achieving a 15% reduction in RMSE compared to previous models. This improvement contributes to faster response times and lower energy consumption in microgrid operation.