Two-Layer Optimization Scheduling of Electric Vehicle Charging and Energy Storage Systems in Microgrids

In the context of the global energy structure transformation, microgrids, as a new type of power system, have garnered widespread attention for their flexibility and efficiency. Electric vehicles as a green transportation tool, introduce significant volatility in charging loads. This paper explores the challenges posed by the volatility of EV charging loads and the conflict in managing energy storage systems on the stability and economic performance of microgrids. It presents an optimization approach and establishes a two-layer optimization model to address the conflicts between charging demand and energy storage management. By employing dynamic scheduling strategies to enhance responsiveness, the paper aims to mitigate the impact of charging fluctuations on the microgrid. A case study using a mixed-line scenario is provided for two-layer optimization modeling. The paper summarizes the key issues and solutions of the research, and based on theoretical and practical needs, identifies future development trends, emphasizing higher precision, stability, and the integration of intelligent scheduling optimization methods.