Wind power producers can benefit from forming coalitions to participate cooperatively in electricity markets. To support such collaboration, various profit allocation rules rooted in cooperative game theory have been proposed. However, existing approaches overlook the lack of coherence among producers regarding forecast information, which may lead to ambiguity in offering and allocations. In this paper, we introduce a ``reconcile-then-optimize'' framework for cooperative market offerings. This framework first aligns the individual forecasts into a coherent joint forecast before determining market offers. With such forecasts, we formulate and solve a two-stage stochastic programming problem to derive both the aggregate offer and the corresponding scenario-based dual values for each trading hour. Based on these dual values, we construct a profit allocation rule that is budget-balanced and stable. Finally, we validate the proposed method through empirical case studies, demonstrating its practical effectiveness and theoretical soundness.

翻译：风电生产商可通过组建联盟协同参与电力市场以获取收益。为支持此类合作，学界已提出多种基于合作博弈理论的利润分配规则。然而，现有方法忽视了生产商间预测信息缺乏一致性的问题，这可能导致报价与分配结果存在歧义。本文提出一种"协调-优化"框架用于协同市场报价：该框架在确定市场报价前，首先将个体预测整合为一致性的联合预测。基于此类预测，我们构建并求解两阶段随机规划问题，以推导每小时交易时段的聚合报价及对应的基于场景的对偶值。依托这些对偶值，我们构建了一种满足预算平衡与稳定性的利润分配规则。最后，通过实证案例研究验证了所提方法的实际效能与理论完备性。