Intelligent Multiobjective NSBGA-II Control of Power Converters in DC Microgrids

In this article, we develop a novel multiobjective controller to regulate the power converters of class dc microgrids connected nonlinear constant loads and linear resistive loads. The suggested control approach uses nondominating sorting binary genetic algorithm (NSBGA-II) directly design on/off switching signal without using pulsewidth modulation technique. minimizes tracking error bus voltage at same time tries reduce total number actions. Thereby, developed tracks desired reference with reduced converter action loss by proper Pareto solution. Moreover, employing NSBGA-II algorithm, it is feasible involve frequency in procedure enhance performance. Exploiting instead conventional (GA) turns continuous surface searching into one, which not only makes more compatible nature but also decreases online computational burden. To illustrate superiority proposed approach, real-time OPAL results are provided.