Research on Multi-Scenario Source-Grid-Load-Storage Optimization and Comprehensive Optimization Strategies Considering User Satisfaction and Economy

With the continuous development and improvement of smart grids, the autonomy of microgrids and users is becoming stronger, making the research and application of microgrid optimization scheduling strategies increasingly important. Therefore, based on the demand side response scheduling strategy, this article establishes a multi-objective optimization model for microgrids with the optimization objectives of maximizing user satisfaction and minimizing microgrid operating costs. At the same time, the existing standard particle swarm optimization algorithm was improved by using a multi-objective improved particle swarm optimization algorithm based on Pareto dominance for solving in multiple scenarios, resulting in multiple non inferior solutions. However, the actual scheduling strategy for microgrids can only choose one. Finally, the ideal solution ranking method based on entropy weight is used to evaluate the non inferior solutions, and the optimal strategy is obtained to ensure the optimization of benefits on both the supply and demand sides.