Double Layer Optimization Scheduling of Multi Area VPPs with Shared Energy Storage

Virtual Power Plant (VPP) aggregates controllable resources such as distributed new energy and flexible loads within a region into a whole, and coordinates and schedules them through virtual power plant agents. To further study the multi energy flow coupling characteristics and coordination scheduling capabilities among virtual power plants in multiple regions, and to improve the utilization rate of new energy in the region. This article introduces SES(SES) into the optimization scheduling of multi region VPPs aggregates gas turbines, gas boilers and other devices, and establishes a dual layer optimization scheduling model for multi region virtual power plants considering uncertainty. To address the complex and difficult problem of solving nonlinear equations in the model, the double-layer model is transformed into a single-layer model using KKT conditions, and the nonlinear conditions are linearized using Big-M method for solution. The simulation was conducted using an improved system, and the results showed that sharing energy storage can effectively reduce the operating costs of multi regional virtual power plants and improve the utilization rate of new energy.