Self-adaptive Genetic Algorithm and Fuzzy Decision Based Multi-objective Optimization in Microgrid with DGs

Microgrid is one practical infrastructure to integrate Distributed Generations (DGs) and local loads. Its optimal operating strategy has aroused great attention in recent years. This paper mainly focuses on the multi-objective optimization of DGs in microgrid by using self-adaptive genetic algorithm (GA) and fuzzy decision. Five objective functions are taken into account comprising voltage offset, transmission loss, construction cost, purchase cost and the environmental cost. In the algorithm, selfadaptation in population size, mutation probability, selection and standardization of objective functions is developed to enhance the speed and efficiency of the algorithm. Moreover, fuzzy decision is applied to determine the final solution. Simulation results show this algorithm can effectively find the optimal solution and improve the real-time control of microgrid, which implies the possibility of potential applications in microgrid energy management system.