Multi-Objective Optimization Scheduling of Microgrids Considering Demand Response

Currently, uncertainty, demand side response, and multi-objective optimization issues of renewable energy have become important research topics in microgrid optimization. An optimization strategy considering economic indicators, security indicators, and demand response is proposed to address these issues. The optimization scheduling uses a complementary power generation method combining diesel engines and energy storage systems to address the uncertainty of large-scale renewable energy grid connection. With the aim of reducing the overall operating costs of microgrids and the power fluctuations between micro grids and the main grid interconnection lines, a coordinated operation model for distributed power generation and demand side load optimization management is established in the context of time-of-use electricity prices. The design problem is solved using the enhanced multi-objective Particle Swarm Optimization method and Pareto optimum solution theory, and the best solution is found using the fuzzy membership function. According to the calculation results, demand response reduces the microgrid's total operating costs by 12.46% when compared to when it is not used, and it also lessens line power fluctuation by 11.11 %, which has positive effects on both the economy and public safety.