Research on a Three-Stage Dynamic Reactive Power Optimization Decoupling Strategy for Active Distribution Networks with Carbon Emissions

Yuezhong Wu (), Yujie Xiong, Xiaowei Peng, Cheng Cai and Xiangming Zheng
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Yuezhong Wu: College of Railway Transportation, Hunan University of Technology, Zhuzhou 412007, China
Yujie Xiong: College of Electrical and Information Engineering, Hunan University of Technology, Zhuzhou 412007, China
Xiaowei Peng: Hunan Kori Convertors Co., Ltd., Zhuzhou 412007, China
Cheng Cai: Hunan Fuze Information Technology Co., Ltd., Changsha 410205, China
Xiangming Zheng: College of Urban and Environmental Sciences, Hunan University of Technology, Zhuzhou 412007, China

Energies, 2024, vol. 17, issue 11, 1-21

Abstract: The reactive power optimization of an active distribution network can effectively deal with the problem of voltage overflows at some nodes caused by the integration of a high proportion of distributed sources into the distribution network. Aiming to address the limitations in previous studies of dynamic reactive power optimization using the cluster partitioning method, a three-stage dynamic reactive power optimization decoupling strategy for active distribution networks considering carbon emissions is proposed in this paper. First, a carbon emission index is proposed based on the carbon emission intensity, and a dynamic reactive power optimization mathematical model of an active distribution network is established with the minimum active power network loss, voltage deviation, and carbon emissions as the satisfaction objective functions. Second, in order to satisfy the requirement for the all-day motion times of discrete devices, a three-stage dynamic reactive power optimization decoupling strategy based on the partitioning around a medoids clustering algorithm is proposed. Finally, taking the improved IEEE33 and PG&E69-node distribution network systems as examples, the proposed linear decreasing mutation particle swarm optimization algorithm was used to solve the mathematical model. The results show that all the indicators of the proposed strategy and algorithm throughout the day are lower than those of other methods, which verifies the effectiveness of the proposed strategy and algorithm.

Keywords: active distribution network; carbon emission; dynamic reactive power optimization; partitioning around medoids clustering algorithm; linear decreasing mutation particle swarm optimization 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: 2024
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