Particle Swarm Optimization Based Dispatching of Source-Grid-Load-Storage with Demand Response

The integrated model of source-grid-load-storage (SGLS) significantly enhances the flexibility and controllability of the power system by integrating the elements of generation, transmission, distribution, consumption, and storage. However, traditional dispatching methods encounter numerous challenges, such as the instability and intermittency of renewable energy supply, along with the optimal utilization of storage systems. To address these challenges, this paper proposes a particle swarm optimization (PSO) based dispatching algorithm for SGLS system considering multi-load demand response (DR). First, cost models of the SGLS system are established as the optimization objectives. Second, the PSO algorithm is utilized to optimize the output of wind turbines, photovoltaics, storage, and load adjustments, thereby achieving system cost savings and efficient utilization of renewable energy. Third, multiple dispatching rules are proposed to further minimize the system cost by comprehensively considering actual operating conditions. Comparative results substantiate the effectiveness of the presented dispatching algorithm.