基于核仁聚类估计和数据驱动分布鲁棒优化的海量异构产消者联盟能量管理策略

随着分布式资源接入技术和可交易能源市场的快速发展，海量异构多能产消者电热能源共享和源荷强不确定性给联盟能量管理带来极大挑战。基于此，提出一种基于核仁聚类估计和数据驱动分布鲁棒优化的海量异构多能产消者联盟能量管理策略。该方法以联盟及个体在多重不确定性影响下的社会福利最大为目标，建立了考虑电热网络动态差异性的海量产消者能量管理模型，以解决联盟能量管理可扩展性、公平性和隐私性难以兼顾的问题。另外，考虑到核仁计算的复杂度和源荷不确定性的不利影响，分别提出了基于高斯混合聚类的核仁估计方法和基于数据驱动Wasserstein距离的分布鲁棒优化模型，实现了模型求解速度与精度的均衡。算例结果表明，所提方法有效提升了产消者联盟在多重不确定性影响下的社会福利，实现了联盟能量管理可扩展性、公平性和隐私性的均衡，促进了更多的产消者参与本地能源点对点(peer-to-peer, P2P)交易。

Energy management strategy for massive heterogeneous prosumers alliance based on nucleolar clustering estimation and data-driven distributionally robust optimization

There has been rapid development of distributed resource access technology and the tradeable energy market. Along with this, thermal energy sharing and strong uncertainty of source load for massive heterogeneous multi-energy producers and consumers bring great challenges to energy management of an alliance. Based on this, this paper proposes an energy management strategy for a massive heterogeneous multi-energy consumer alliance based on nucleolar cluster estimation and data-driven optimization of a distributed robust system. With the objective of maximizing the social welfare of the alliance and individuals under the influence of multiple uncertainties, the energy management model of a massive heterogeneous consumer alliance considering the dynamic differences of the electric heating network is established. This is to solve the problem that the scalability, fairness and privacy of alliance energy management are difficult to take into account. In addition, considering the complexity of nucleolar computation and the adverse effects of source load uncertainty, this paper proposes a nucleolar estimation method based on Gaussian mixture clustering and distributed robust optimization model based on data-driven Wasserstein distance, respectively, to achieve a balance between model solving speed and accuracy. The numerical results show that the proposed method effectively improves the social welfare of the producers and consumers alliance under the influence of multiple uncertainties, achieves the balance of scalability, fairness and privacy of the energy management of the alliance, and promotes more producers and consumers to participate in local energy peer-to-peer (P2P) transactions.