The internal energy optimization within a single entity of industrial users, base stations, and charging stations is constrained by local power supply and demand limitations, resulting in low utilization of flexible resources such as energy storage and insufficient energy utilization efficiency. To address these issues, an energy sharing and interactive optimization method is proposed for industrial users, base stations, and charging stations based on the quantification of their complementarity and a game-based pricing incentive mechanism. First, a complementary quantification model is developed based on the analysis of the characteristics of industrial users, base stations, and charging stations, using the standard deviation of net load as a complementary indicator. Then, considering the adjustable capabilities of air conditioning and electric vehicles, as well as the proactive decision-making abilities of industrial users, charging stations, and base stations, a master-slave game-based pricing model is established to incentivize the sharing of energy storage and energy interaction among these entities. Next, incorporating 0-1 integer variables, a solution method utilizes the adaptive differential evolution algorithm combined with the mixed-integer optimization theory. Finally, case studies validate that optimizing the energy storage and energy dispatch of industrial users, base stations, and charging stations in different time periods can effectively leverage their complementarity, enhance the economic benefits of each entity, improve the utilization of idle flexible resources, and enhance the overall energy self-consistency of the system.
