A Load Control User Combinatorial Optimization Method Considering Electric Vehicle and Temperature-Controlled Load Clusters
As the construction of the new power system continues to deepen, the power system faces such problems as large peak-to-valley difference and high volatility, and the use of user-side resources to participate in load control is one of the important initiatives to solve the above-said problems. In thi...
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State Grid Energy Research Institute
2025-03-01
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| Series: | Zhongguo dianli |
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| Online Access: | https://www.electricpower.com.cn/CN/10.11930/j.issn.1004-9649.202402070 |
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| author | Siwei LI Zhongping XU Long YU Lishi DU Liang YUE Xirun ZHANG Xiaoming WANG |
| author_facet | Siwei LI Zhongping XU Long YU Lishi DU Liang YUE Xirun ZHANG Xiaoming WANG |
| author_sort | Siwei LI |
| collection | DOAJ |
| description | As the construction of the new power system continues to deepen, the power system faces such problems as large peak-to-valley difference and high volatility, and the use of user-side resources to participate in load control is one of the important initiatives to solve the above-said problems. In this paper, a load control user combinatorial optimization method considering electric vehicle (EV) and temperature-controlled load clusters is proposed. Firstly, a hierarchical control method is used to aggregate individual EVs and temperature-controlled load clusters, and the aggregated clusters are divided into peak load shifting type and peak load shedding type according to their willingness to participate in load control types, and their respective user load control models are established. Secondly, a three-stage rebound load model is constructed to solve the load rebound problem after peak load shifting users participate in load control. And then, a load control influence function is established with consideration of the influence degree of users participating in load control. Finally, the composition of user groups participating in peak load shifting and shedding and the adjustment amount of user load are optimized with the minimum load control influence, minimum network loss and minimum load fluctuation as multi-objectives. While meeting the demand of load control, the proposed method can effectively inhibit the new peak load caused by the rebound of load after users participating in load control, as a result, realizing the good interaction of supply and demand between distributed load resources and the power system. |
| format | Article |
| id | doaj-art-2428fb4ce02f4c8693fb9495693d0553 |
| institution | DOAJ |
| issn | 1004-9649 |
| language | zho |
| publishDate | 2025-03-01 |
| publisher | State Grid Energy Research Institute |
| record_format | Article |
| series | Zhongguo dianli |
| spelling | doaj-art-2428fb4ce02f4c8693fb9495693d05532025-08-20T02:48:27ZzhoState Grid Energy Research InstituteZhongguo dianli1004-96492025-03-01583869710.11930/j.issn.1004-9649.202402070zgdl-57-09-lisiweiA Load Control User Combinatorial Optimization Method Considering Electric Vehicle and Temperature-Controlled Load ClustersSiwei LI0Zhongping XU1Long YU2Lishi DU3Liang YUE4Xirun ZHANG5Xiaoming WANG6Key Laboratory of Smart Grid of Ministry of Education (Tianjin University), Tianjin 300072, ChinaBeijing Fibrlink Communications Co., Ltd., Beijing 100071, ChinaBeijing Fibrlink Communications Co., Ltd., Beijing 100071, ChinaBeijing Fibrlink Communications Co., Ltd., Beijing 100071, ChinaBeijing Fibrlink Communications Co., Ltd., Beijing 100071, ChinaBeijing Fibrlink Communications Co., Ltd., Beijing 100071, ChinaElectric Power Research Institute of State Grid Anhui Electric Power Company, Hefei 230061, ChinaAs the construction of the new power system continues to deepen, the power system faces such problems as large peak-to-valley difference and high volatility, and the use of user-side resources to participate in load control is one of the important initiatives to solve the above-said problems. In this paper, a load control user combinatorial optimization method considering electric vehicle (EV) and temperature-controlled load clusters is proposed. Firstly, a hierarchical control method is used to aggregate individual EVs and temperature-controlled load clusters, and the aggregated clusters are divided into peak load shifting type and peak load shedding type according to their willingness to participate in load control types, and their respective user load control models are established. Secondly, a three-stage rebound load model is constructed to solve the load rebound problem after peak load shifting users participate in load control. And then, a load control influence function is established with consideration of the influence degree of users participating in load control. Finally, the composition of user groups participating in peak load shifting and shedding and the adjustment amount of user load are optimized with the minimum load control influence, minimum network loss and minimum load fluctuation as multi-objectives. While meeting the demand of load control, the proposed method can effectively inhibit the new peak load caused by the rebound of load after users participating in load control, as a result, realizing the good interaction of supply and demand between distributed load resources and the power system.https://www.electricpower.com.cn/CN/10.11930/j.issn.1004-9649.202402070distributed load resourcestemperature control load clusterload reboundload controlcombinatorial optimization |
| spellingShingle | Siwei LI Zhongping XU Long YU Lishi DU Liang YUE Xirun ZHANG Xiaoming WANG A Load Control User Combinatorial Optimization Method Considering Electric Vehicle and Temperature-Controlled Load Clusters Zhongguo dianli distributed load resources temperature control load cluster load rebound load control combinatorial optimization |
| title | A Load Control User Combinatorial Optimization Method Considering Electric Vehicle and Temperature-Controlled Load Clusters |
| title_full | A Load Control User Combinatorial Optimization Method Considering Electric Vehicle and Temperature-Controlled Load Clusters |
| title_fullStr | A Load Control User Combinatorial Optimization Method Considering Electric Vehicle and Temperature-Controlled Load Clusters |
| title_full_unstemmed | A Load Control User Combinatorial Optimization Method Considering Electric Vehicle and Temperature-Controlled Load Clusters |
| title_short | A Load Control User Combinatorial Optimization Method Considering Electric Vehicle and Temperature-Controlled Load Clusters |
| title_sort | load control user combinatorial optimization method considering electric vehicle and temperature controlled load clusters |
| topic | distributed load resources temperature control load cluster load rebound load control combinatorial optimization |
| url | https://www.electricpower.com.cn/CN/10.11930/j.issn.1004-9649.202402070 |
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