考虑协同增量的微电网集群划分及优化分配方法

Hongbin Zhang, Weisheng Liu, Shumin Sun, YU Peng, Chuanzhi Cui
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引用次数: 0

摘要

在可再生能源渗透率较高的配电网中,多个微网协同运行可构成微网集群。实现了微网集群中各微网分布式发电机(DG)和储能系统(ESS)的容量优化,提高了配电网的经济运行。本文提出一种考虑协同增量的微网集群划分与优化分配方法:建立考虑可再生能源消耗的微网规划模型,实现各微网年等效成本最低。考虑节点耦合度,提出了区域配电网集群划分方法。将同一分区内具有协同增量进行联合运行的微网划分为微网集群。最后,建立了两层微网集群优化模型,用于微网集群联合规划。上层模型的目标是优化微网集群的容量分配,下层是考虑微网集群运行成本的联合优化模型。通过从IEEE-33系统合理扩展的42节点系统的仿真结果,验证了所提微网集群规划方法的有效性和优越性。结果表明,微电网集群规划能够实现配电网较好的经济运行和高比例可再生能源就近消纳。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Microgrid Cluster Division and Optimal Allocation Method Considering Cooperative Increment
In the distribution network with a high proportion of renewable energy penetration, the cooperative operation of multiple microgrids can constitute a microgrid cluster. The capacity optimization of distributed generator (DG) and energy storage system (ESS) of each microgrid in the microgrid cluster is realized, which can improve distribution network economic operation. This paper proposes a microgrid cluster division and optimal allocation method considering cooperative increment: The microgrid planning model considering renewable energy consumption is established, achieving the lowest the lowest annual equivalent cost of each microgrid. Considering the node coupling degree, a regional distribution network cluster partition is presented. Microgrids that are in the same partition and have cooperative increments for joint operation are divided into microgrid clusters. Finally, a two-layer microgrid cluster optimization model is established for joint planning of microgrid cluster. The objective of upper layer model is to optimize capacity allocation of microgrid cluster, and the lower layer is a joint optimization model considering the operation cost of microgrid cluster. The effectiveness and superiority of the proposed microgrid cluster planning method is verified by simulation results of the 42-node system reasonably expanded from IEEE-33 system. The results show that the microgrid cluster planning can achieve better economic operation of distribution network and the nearby consumption of high proportion of renewable energy.
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