Game theory based energy sharing schemes emerged in recent years to incentivize efficient management of the increasing amount of distributed energy resources. Among these, cooperative game theoretic schemes provide detailed financial incentives on the individual prosumer level. The nucleolus, a mechanism to allocate these financial incentives, has been proven to guarantee the prosumers’ willingness to participate. However, the computation time of the nucleolus increases exponentially with the number of participants, strictly limiting the size of this scheme. This study proposes to incorporate clustering techniques to estimate the nucleolus at reduced computation times, where a novel marginal contribution profile is used as the clustering features. A stratified random sampling based approach is formulated to evaluate the estimation performance, showing that the proposed method is able to scale up the cooperative energy management scheme from less than 15 players to over 100 players while maintaining high accuracy of the nucleolus estimation.

中文翻译：

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使用生产者聚类扩大基于合作博弈论的能源管理

近年来出现了基于博弈论的能源共享方案，以激励人们对越来越多的分布式能源进行有效管理。其中，合作博弈理论方案在个人生产者层面提供了详细的经济激励措施。核仁是分配这些经济奖励措施的一种机制，已被证明可以保证生产者的参与意愿。但是，核仁的计算时间随参与者的数量成指数增加，从而严格限制了该方案的规模。这项研究建议采用聚类技术来估计减少的计算时间的核仁，其中一种新型的边际贡献图被用作聚类特征。制定了一种基于分层随机抽样的方法来评估估计性能，