2025/10/14 by Honglin Wen, Pierre Pinson, Wen, Honglin +1
Engineering · #Ambiguity #Applications (stat.AP) #Dual (grammatical number) #Electric Power System Optimization #Electricity market #FOS: Computer and information sciences #FOS: Electrical engineering #Inefficiency #Pooling #Probabilistic logic #Profit (economics) #Shapley value #Systems and Control (eess.SY) #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2510.12382
published in arXiv (Cornell University) (Cornell University)
openalex publication_date 2025/10/14 · openalex created_date 2025/10/17 · openalex updated_date 2026/07/28
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.