发表机构
University of Wisconsin-Madison（威斯康星大学麦迪逊分校）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
该研究针对分布式能源资源参与批发市场的痛点，提出多智能体滚动时域博弈框架，实现公平的点对点联合投标，在PJM市场应用中提升了机组利润、降低了成本与弃电率。
AI 中文摘要
电解槽、电池储能系统等电化学分布式能源资源（DER）会消耗大量电力，直接从批发市场购电可大幅降低运营成本。然而，参与这些市场需要达到最低投标规模，单个中小型机组难以满足，将多个机组组合为单一主体投标既能突破该门槛，又能让各机组利用自身低成本可再生能源发电。常见解决方案是聘请第三方聚合商，但聚合商会收取佣金，且其求解的集中式优化往往偏向特定机组。更公平的替代方案是点对点（P2P）参与，即机组组成自治团体共同投标，无需中央机构。由于各自利机组不愿共享私有数据，协调问题最适合表述为博弈论分布式优化问题。不过，现有P2P方法仅针对单回合现货市场，未考虑实际批发市场的两阶段结构——参与者提前一天承诺，再实时持续调整。我们提出两阶段滚动时域广义纳什均衡（GNE）博弈以填补该空白：各机组每5分钟在滚动的1小时时域内重新优化策略，同时团体整体满足两个市场阶段的要求；机组仅交换公开可见的总功率，从不共享私有成本或生产数据。我们将该方法应用于PJM市场的6机组集群，与单独参与相比，其利润提高37%、电力成本降低29%、可再生能源弃电减少92%，且所有机组均获益。
英文摘要
Electrochemical distributed energy resources (DERs), such as electrolyzers and battery energy storage systems, consume large amounts of electricity. Buying that power directly from wholesale markets can sharply reduce operating costs. Accessing these markets, however, requires a minimum bid size that individual small or medium-scale units struggle to meet. Grouping several units to bid as a single participant clears this barrier while letting each unit use its own low-cost renewable generation. The common remedy is to hire a third-party aggregator, but aggregators charge commissions and solve a centralized optimization that often favors certain units over others. A fairer alternative is peer-to-peer (P2P) participation, where units form a self-governing group and bid jointly with no central authority. Because each self-interested unit is unwilling to share private data, coordination is best posed as a game-theoretic distributed optimization problem. Existing P2P methods, however, address only single-round spot markets and ignore the two-stage structure of real wholesale markets, where participants commit a day ahead and continuously adjust in real time. We close this gap with a two-stage receding-horizon generalized Nash equilibrium (GNE) game. Each unit re-optimizes its strategy every five minutes over a rolling one-hour horizon, while the group satisfies both market stages collectively. Units exchange only publicly visible aggregate power, never private cost or production data. We apply the approach to a six-unit fleet on the PJM market. It delivers 37% higher profit, 29% lower electricity cost, and 92% less renewable curtailment than individual participation, with every unit better off.
