Research on the Design and Optimization Strategy of Load Regulation Function of Virtual Power Plant

As the global energy structure transforms to renewable energy, virtual power plants (VPP) have become an important solution to improve the flexibility and stability of the power grid. This article focuses on the design of VPP load regulation function, analyzes the current research status at home and abroad, and points out the current shortcomings in load forecasting cross-time scale optimization and robust strategy design. Focusing on the integrated project of Jiangxi virtual power plants, a full load regulation process system is designed, including power consumption load forecasting and cluster analysis, multi-scenario bidirectional long short-term memory network (BiLSTM) prediction model construction, and VPP load regulation scenario strategy system design. Innovative points such as hierarchical design and real-time rolling prediction are proposed, and with the help of experimental analysis, the significant advantages of the model based on CPLEX solution in load regulation accuracy and economic benefits are verified. The research results provide technical support and decision-making basis for the application of virtual power plants in improving the flexibility, stability and economics of power systems.