A Novel Refined Regulation Method with Modified Genetic Commutation Algorithm to Reduce Three-Phase Imbalanced Ratio in Low-Voltage Distribution Networks

Dazhao Liu, Zhe Liu, Ti Wang, Zhiguang Xie, Tingting He (), Aixin Dai and Zhiqiang Chen
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Dazhao Liu: State Grid Beijing Electric Power Company, No. 41 Qianmen West Street, Beijing 100031, China
Zhe Liu: State Grid Beijing Electric Power Company, No. 41 Qianmen West Street, Beijing 100031, China
Ti Wang: State Grid Beijing Electric Power Company, No. 41 Qianmen West Street, Beijing 100031, China
Zhiguang Xie: State Grid Beijing Electric Power Company, No. 41 Qianmen West Street, Beijing 100031, China
Tingting He: School of Electrical Engineering, Beijing Jiaotong University, No. 3 Shangyuan Cun, Haidian District, Beijing 100044, China
Aixin Dai: School of Electrical Engineering, Beijing Jiaotong University, No. 3 Shangyuan Cun, Haidian District, Beijing 100044, China
Zhiqiang Chen: School of Electrical Engineering, Beijing Jiaotong University, No. 3 Shangyuan Cun, Haidian District, Beijing 100044, China

Energies, 2023, vol. 16, issue 23, 1-16

Abstract: The three-phase imbalance in low-voltage distribution networks (LVDNs) seriously threatens the security and stability of the power system. At present, a standard solution is automatic phase commutation, but this method has limitations because it does not address the branch imbalance and premature convergence or instability of the commutation algorithm. Therefore, this paper proposes a novel refined regulation commutation system, combined with a modified optimized commutation algorithm, and designs a model and simulation for feasibility verification. The refined regulatory model incorporates branch control units into the traditional commutation system. This effectively disperses the main controller’s functions to each branch and collaborates with intelligent fusion terminals for precise adjustment. The commutation algorithm designed in this paper, combined with the above model, adopts strategies such as symbol encoding, cubic chaotic mapping, and adaptive adjustment based on traditional genetic algorithms. In addition, in order to verify the effectiveness of the proposed method, this paper establishes a mathematical model with the minimum three-phase imbalance and commutation frequency as objectives and establishes a simulation model. The results of the simulation demonstrate that this method can successfully lower the three-phase imbalance of the low-voltage distribution network. It leads to a decrease of the main circuit’s three-phase load imbalance rate from 27% to 6% and reduces each branch line’s three-phase imbalance ratio to below 10%. After applying the method proposed in this paper, the main and branches circuit three-phase imbalance are both lower than the limit ratio of the LVDNs, which can improve the quality and safety of electricity consumption. Additionally, the results also prove that the commutation algorithm under this method has faster convergence speed, better application effect, and better stability, which has promotion and application value.

Keywords: low-voltage distribution networks; three-phase imbalance; refined regulation commutation; cubic adaptive genetic 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
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