[1]CHENG Zixia,TANG Xing,CHAI Xuzheng,et al.Optimized Configuration of Two Layers of Smart Energy Storage Soft Switches for Distribution Networks Considering Demand Response[J].Journal of Zhengzhou University (Engineering Science),2026,47(XX):1-10.[doi:10.13705/j.issn.1671-6833.2025.05.015]
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Journal of Zhengzhou University (Engineering Science)[ISSN
1671-6833/CN
41-1339/T] Volume:
47
Number of periods:
2026 XX
Page number:
1-10
Column:
Public date:
2026-09-10
- Title:
-
Optimized Configuration of Two Layers of Smart Energy Storage Soft Switches for Distribution Networks Considering Demand Response
- Author(s):
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CHENG Zixia1 ; TANG Xing1 ; CHAI Xuzheng2 ; GUO Zichan1 ; YAO Wenbo1
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1. Schoo l of Electrical and Information Engineering, Zhengzhou University, Zhengzhou 450001, China; 2. State Grid Xuchang Power Supply Company, Xuchang 461000, China
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- Keywords:
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soft open point integrated with energy storage system; Frank-Copula function; two-layer planning; whale optimization algorithms; second-order cone planning
- CLC:
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TM751TM744TM732
- DOI:
-
10.13705/j.issn.1671-6833.2025.05.015
- Abstract:
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Aiming at the problems of increasing network losses and voltage overruns faced by power systems containing a high proportion of new energy, a two-layer planning strategy of soft open point integrated with energy storage system (E-SOP) for distribution networks considering demand response is proposed. Firstly, the typical scenarios of wind power output are generated based on Frank-Copula function considering the relevant characteristics of wind power output. Secondly, a two-layer planning model of E-SOP was established, where the upper layer takes the objective of lowest annual comprehensive operating cost of the distribution network for the siting and capacity setting of E-SOP, and the lower layer takes the demand response participation into consideration, and the operation optimization is carried out with the objective of the minimum operating cost of each scenario, and adopts the multi-strategy improved whale optimization algorithm (MIWOA) and Second-order Conic Programming (SOCP) are used to solve the model. Finally, the IEEE33-node systems are used for example analysis, and the simulation results showed that the annual integrated costs of the systems are reduced by 7.94%, respectively, which verifies that the proposed scheme could effectively improve the stability and economy of distribution network operation.