Research on Dual-Layer Coordinated Optimization Scheduling Model of Power System Based on Flow Battery for Renewable Energy Integration

The integration of intermittent and fluctuating renewable energy sources such as wind and solar power into the power grid poses significant challenges for load balancing in the electricity system. To address the insufficient peak load regulation capability after the large-scale integration of renewable energy sources, a dual-layer coordinated optimization scheduling model is proposed by leveraging the rapidly evolving electrochemical energy storage device, namely the flow battery. In the first layer of the model, the objective is to enhance the overall peak load regulation capability of the power system by flattening load peaks and filling load valleys to improve the system's flexibility in load regulation and balance the supply-demand fluctuations. In the second layer of the model, the goal is to minimize the total cost of the power system operation while satisfying the optimization results of the first layer. This is achieved by re-planning the output of each component, including thermal power generation, renewable energy generation, and flow battery energy storage, to minimize the difference between costs and profits, thus reducing expenses. Finally, an improved IEEE 30-node system is used as a case study for simulation validation. The results demonstrate that with the integration of renewable energy sources, leveraging flow batteries for system load regulation enhances the overall peak load regulation capability and reduces the total cost of the system.