In this work, a Stackelberg game theoretic framework is proposed for trading energy bidirectionally between the demand-response (DR) aggregator and the prosumers. This formulation allows for flexible energy arbitrage and additional monetary rewards while ensuring that the prosumers' desired daily energy demand is met. Then, a scalable (with the number of prosumers) approach is proposed to find approximate equilibria based on online sampling and learning of the prosumers' cumulative best response. Moreover, bounds are provided on the quality of the approximate equilibrium solution. Last, real-world data from the California day-ahead energy market and the University of California at Davis building energy demands are utilized to demonstrate the efficacy of the proposed framework and the online scalable solution.
翻译：在此研究中，提出了一个斯塔克伯格博弈理论框架，用于在需求响应（DR）聚合器和自给自足者之间双向交易能源。该公式允许进行灵活的能源套利和额外的货币奖励，同时确保自给自足者所需的每日能源需求得到满足。然后，提出了一种可扩展的方法来基于自给自足者累积最佳响应的在线采样和学习来寻找近似均衡。此外，提供了关于近似均衡解质量的界限。最后，使用来自加利福尼亚日前能源市场和加州大学戴维斯分校建筑能源需求的实际数据来证明所提出的框架和在线可扩展解决方案的有效性。
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