A Collaborative Planning Method for the Source and Grid in a Distribution System That Considers Risk Measurement

Jiahao Deng, Lingxue Lin (), Yongjie Zhang and Yuxin Ma
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Jiahao Deng: College of Electric Power, South China University of Technology, Guangzhou 510640, China
Lingxue Lin: College of Electric Power, South China University of Technology, Guangzhou 510640, China
Yongjie Zhang: College of Electric Power, South China University of Technology, Guangzhou 510640, China
Yuxin Ma: College of Electric Power, South China University of Technology, Guangzhou 510640, China

Energies, 2023, vol. 16, issue 15, 1-21

Abstract: The existing distribution system planning methods do not fully consider improving power supply capacity and reliability through the coordination of multiple planning factors, and they are not comprehensive enough in quantifying planning risks. Therefore, this paper proposes a collaborative planning method for sources and networks that considers risk measurement. A multi-layer planning model is first constructed that includes a grid planning layer, a power planning layer, a switch planning layer, and an operation optimization layer. In the model, a risk measurement method combining opportunity constraints and conditional value-at-risk objectives is used to comprehensively assess the risk of the node voltage and branch current exceeding the limit caused by load uncertainty. Then, a solution strategy based on a genetic algorithm and a sparrow search algorithm is proposed to coordinate the contradiction between the solution time and the accuracy of the multi-layer model. Finally, taking a planned area to be expanded as an example, the results show that compared to the existing collaborative planning methods for sources and networks, the proposed method in this paper reduces the planning risks caused by load uncertainty by more than 50% and increases the annual net income of the power distribution company and the DG operators by RMB 1.5 million and RMB 1.1 million, respectively.

Keywords: a collaborative planning for the source and gird; chance constraints; conditional value at risk; genetic algorithm; sparrow search algorithm (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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