Loss Reduction Potential Mining Method for Distribution Networks Based on Improved Genetic Algorithm

Large-scale access of distributed PV to the power grid has become a future trend, which is easy to cause problems such as power flow reversal, resulting in an increase in system line loss. In this paper, a method for mining the loss reduction potential of the distribution network based on the improved genetic algorithm is proposed, the distributed photovoltaic and energy storage components are selected as the reactive power compensation devices, and the multi-objective function is established by embodying the sub-objectives in the form of penalty functions, and the loss reduction potential and related optimization parameters of the distribution network are finally obtained based on the improved genetic algorithm, and the simulation verification is carried out by the IEEE30 node test system. The results show that the proposed method can obtain the potential loss reduction potential of the distribution network.

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Publication Details

Published
2024-09-27
DOI
https://doi.org/10.1109/icepg63230.2024.10775856
Primary Topic
Power Systems and Technologies
Type
article
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article

Loss Reduction Potential Mining Method for Distribution Networks Based on Improved Genetic Algorithm

George Yin, Tao Shen, Wenguang Zhao, Jingyi Ni
Power Systems and Technologies
article

Loss Reduction Potential Mining Method for Distribution Networks Based on Improved Genetic Algorithm

George Yin, Tao Shen, Wenguang Zhao, Jingyi Ni
article en

Abstract

Large-scale access of distributed PV to the power grid has become a future trend, which is easy to cause problems such as power flow reversal, resulting in an increase in system line loss. In this paper, a method for mining the loss reduction potential of the distribution network based on the improved genetic algorithm is proposed, the distributed photovoltaic and energy storage components are selected as the reactive power compensation devices, and the multi-objective function is established by embodying the sub-objectives in the form of penalty functions, and the loss reduction potential and related optimization parameters of the distribution network are finally obtained based on the improved genetic algorithm, and the simulation verification is carried out by the IEEE30 node test system. The results show that the proposed method can obtain the potential loss reduction potential of the distribution network.

Changsha University of Science and Technology (CN)
Openalex Percentile: Top 80%
Power Systems and Technologies
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