Coordinated Optimization Dispatch Model of Industrial Load and Shared Energy Storage in Virtual Power Plant Clusters

This paper proposes a multi-virtual power plant dispatch model based on coordinated optimization of industrial flexible loads and shared energy storage, aiming to achieve precise scheduling of three virtual power plants through a mixed-integer programming approach. In the model, industrial flexible loads are classified into three categories: transferable, reducible, and shiftable, and are jointly optimized with the shared energy storage system to achieve peak shaving, valley filling, and cost reduction. To solve the proposed optimization model, the branch and bound method is employed to ensure global optimality of the solution. The simulation results demonstrate that the coordinated adjustment of industrial flexible loads and the efficient utilization of shared energy storage significantly enhance the peak shaving and valley filling effects of the optimized power load curve, while effectively reducing daily operating costs and dependency on the grid. This study provides a theoretical foundation for coordinated optimization among multiple virtual power plants and flexible industrial load response, offering a feasible solution for constructing an efficient and economically viable new power system.