Optimal Allocation of Energy Storage in Distribution Networks Based on Electric Common Information Model

Xiao WANG , Jing ZHANG , Xiao DU , Xuehao HE , Wen ZHANG , Biao ZHAO , Qing LIU

›› 2024, Vol. 18 ›› Issue (5) : 112 -123.

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›› 2024, Vol. 18 ›› Issue (5) : 112 -123. DOI: 10.13648/j.cnki.issn1674-0629.2024.05.011
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Optimal Allocation of Energy Storage in Distribution Networks Based on Electric Common Information Model

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Abstract

Construction of energy storage systems for new power system is an effective means to improve the accommodation of distributed renewable energy and the quality of power supply. The existing research on energy storage planning doesn’t fully utilize the available information from actual distribution automation system, and the configuration results are difficult to apply to actual power grids. Arming at this problem, an optimal allocation method of energy storage based on electric common information model (CIM/e) is proposed. Firstly, the praising approach for CIM/XML data is proposed to realize topology identification and reconstruction of the power flow model for actual distribution network. Secondly, an energy storage optimization configuration model is established, which considers economic and power quality indexes and embedded power flow constraints. This model realizes the integrated design for system operation and planning, providing the optimization of energy storage location and capacity. Finally, two practical power distribution systems with two different voltage levels in southern China are simulated to verify the effectiveness of the proposed method.

Keywords

energy storage allocation / distribution network planning / power flow model / electric common information model

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Xiao WANG,Jing ZHANG,Xiao DU,Xuehao HE,Wen ZHANG,Biao ZHAO,Qing LIU. Optimal Allocation of Energy Storage in Distribution Networks Based on Electric Common Information Model. 2024, 18(5): 112-123 DOI:10.13648/j.cnki.issn1674-0629.2024.05.011

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Funding

the National Natural Science Foundation of China(52207134)

the Science and Technology Project of China Southern Power Grid Co., Ltd(YNKJXM20222105)

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