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：本文提出了一种基于Stackelberg博弈框架的方法，用于实现需求响应（DR）聚合器与产消者之间的双向能源交易。该公式化方法允许灵活的能量套利和额外货币奖励，同时确保满足产消者期望的日能源需求。随后，提出了一种与产消者数量规模可扩展的方法，通过在线采样和学习产消者的累积最优响应来寻找近似均衡解。此外，给出了近似均衡解质量的界。最后，利用加州日前能源市场的真实数据以及加州大学戴维斯分校的建筑能源需求数据，验证了所提框架和在线可扩展解法的有效性。