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Bi-level Distributed Optimal Dispatch of Micro Gird Clusters Based on Mutual Communication

机译:基于相互通信的微观群体双级分布式最优分发

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Micro Gird Cluster (MGC), connecting to the medium or low voltage distribution network, usually contains certain number of Micro Grids, distributed generators, energy storages and loads. Considering coordinated operation in MGC, this paper proposes a hierarchical control architecture- the upper layer operated in distributed mode among multiple MGs and the lower layer were controlled by each micro grid center. This hierarchical architecture not only shows the excellent features of distributed control, but also integrates the advantages of centralized control. According to this hierarchical architecture, bi-level distributed optimal dispatch of MGC is analyzed. With the aim of minimizing MGC total costs in upper layer and minimizing each Micro-Grid costs in lower layer, bi-level optimal mathemat-ic model take global and local aims into account synthetically. The distributed primal-dual sub-gradient algorithm is designed to solve the upper layer optimal model, alternating gradient iteration algorithm for the lower optimization model. Simulation cases show that bi-level distributed optimal mathematic model successfully fulfill the aim of coordinated operation in MGC, and distributed primal-dual sub-gradient algorithm is an effective solution to this optimal model.
机译:连接到介质或低压配电网络的微观群(MGC)通常包含一定数量的微网格,分布式发电机,能量存储器和负载。考虑到MGC中的协调操作,本文提出了分层控制架构 - 在多个MGS之间以分布式模式操作的上层由每个微网格中心控制。此分层架构不仅显示了分布式控制的优异功能,还集中了集中控制的优点。根据该层级架构,分析了MGC的双级分布式最佳调度。目的是最小化上层的MGC总成本,最大限度地减少较低层中的每个微电网成本,双层最佳数学Mathemat-IC模型在综合地考虑到全球和本地目标。分布式原始双梯度算法旨在解决较低优化模型的上层最优模型,交替梯度迭代算法。仿真情况表明,双级分布式最优数学模型成功满足MGC中协调操作的目的,分布式原始 - 双梯度算法是对该最佳模型的有效解决方案。

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