Optimal Siting and Sizing of Distributed PV-storage in Distribution Network Based on Cluster Partition

被引：0
|
作者：
Ding M. [1 ]
Fang H. [1 ]
Bi R. [1 ]
Liu X. [1 ]
Pan J. [2 ]
Zhang J. [1 ]
机构：
[1] Anhui Provincial Renewable Energy Utilization and Energy Saving Laboratory, Hefei University of Technology, Hefei, 230009, Anhui Province
[2] State Grid Anhui Electric Power Co. Ltd., Hefei, 230061, Anhui Province
来源：
Zhongguo Dianji Gongcheng Xuebao/Proceedings of the Chinese Society of Electrical Engineering | 2019年 / 39卷 / 08期
基金：
国家重点研发计划;
关键词：
Bi-level particle swarm optimization algorithm; Cluster partition; Distributed photovoltaic generation; Distribution network; Energy storage system; Siting and sizing;
D O I：
10.13334/j.0258-8013.pcsee.180757
中图分类号：
学科分类号：
摘要：
Since the conventional distributed generation (DG) planning methods are difficult to meet the requirements of operation and zonal control in distribution network systems, a novel cluster-based DG planning approach was proposed. First, the distribution network was divided into several partitions considering the system network structure and the load characteristics, thus conducting a hierarchical and partitioned network structure. On this basis, a bi-level coordinated planning model was developed to realize the optimal siting and sizing of the distributed photovoltaic (DPV)-storage system. Specifically, in upper-layer, an annual comprehensive cost optimization model was built to determine the installation capacities of DPV and storage as well as the power of storage in each cluster. In lower-layer, the minimization of the network loss was considered as the aim to obtain the installation capacity of DPV in each node and the location of storage within every cluster. Finally, a bi-level hybrid particle swarm optimization algorithm embedded power flow was employed to solve the established models iteratively. Simulation tests carried out on a certain 10 kV actual distribution system have verified the feasibility of the established models and the effectiveness of the proposed solving algorithm. © 2019 Chin. Soc. for Elec. Eng.
引用
收藏
页码：2187 / 2201
页数：14
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