通过斯塔克尔伯格博弈实现柔性负荷与风能的协同以促进可再生能源整合和经济效率

Abstract The modern electric grid enables prosumers’ participation in energy management by integrating flexible loads like electric vehicles (EVs) and battery energy storage systems (BESS) via demand response (DR). However, the main challenge lies in motivating EV owners to adjust their low-cost charging plans to align with distributed generation, e.g., wind and photovoltaic (PV) power. This requires a reward system with more attractive financial incentives than the customers’ initially planned savings. From the mathematical standpoint, the primary challenge lies in finding the dual of the problem due to the presence of several disjoint or overlapping time-based exceptions in the modeling of EVs and BESS. This study aims to optimize the synergy between PV, wind, and flexible EV loads via an incentive-based DR framework. A bi-level model is proposed and solved using a Stackelberg game between a wind-farm aggregator and customers, reducing customer costs and improving wind-load matching. The proposed bi-level model is transformed into a single-level equivalent through a dual formulation, addressing the complexities of overlapping time-based exceptions causing redundancies. Validated across seasons, the results highlight the DR’s success in enhancing aggregator and customer outcomes. In an example case, customer energy costs dropped by up to 146.56 €/day, and the aggregator reduced the wind energy-load mismatch by up to 356 kWh in one day. Results show that greater load flexibility and wind capacity enhance economic and energy management outcomes, highlighting the impact of scalable DR opportunities.