Optimization scheduling method of virtual power plant with integrated Source-Grid-Load-Storage based on CS-GWO algorithm

Virtual Power Plant (VPP) participate in power system operations and market transactions by aggregating flexible resources. Specifically, Source-Grid-Load-Storage Integrated Virtual Power Plant (SGLS- VPP) coordinate the joint regulation of power users with different types, e.g. distributed power generation, battery energy storage systems, and controllable industrial loads. However, the energy dispatch of SGLS- VPP is a complex problem, involving multi-objective optimization and a trade-off between economic benefits and user comfort. This study develops a comprehensive model to characterize the operational and economic features of internal resources within the VPP. A hybrid heuristic algorithm, which integrates the Cuckoo Search algorithm with the Grey Wolf Optimizer, is employed to derive the joint control strategy for the VPP. The proposed model is validated through a case study of an incremental distribution network in Hunan, China. The system under investigation achieves an 16.03% increase in operator revenue without compromising user comfort. The results demonstrate the effectiveness of the model and provide a practical approach for VPP to realize further sustainable operation.