Phase sequence optimization of a distribution network based on improved NSGA-3 and unbalanced power flow

被引：0

作者：

Ding S. ^{[1
]}

Cui K. ^{[1
]}

Hang J. ^{[1
]}

Wang Z. ^{[2
]}

Bao H. ^{[3
]}

机构：

[1] School of Electrical Engineering and Automation, Anhui University, Hefei

[2] State Grid Anhui Electric Power Co., Ltd., Dispatching Center, Hefei

[3] Nanning Power Supply Bureau, Guangxi Power Grid Co., Ltd., Nanning

来源：

Dianli Xitong Baohu yu Kongzhi/Power System Protection and Control | 2023年 / 51卷 / 03期

基金：

中国国家自然科学基金;

关键词：

NSGA-3; phase sequence optimization; three phase unbalance in the substation distribution network; unbalanced power flow calculation;

D O I：

10.19783/j.cnki.pspc.220582

中图分类号：

学科分类号：

摘要：

There are many single-phase loads in the low-voltage distribution network, such that an unbalanced three-phase load will increase the line loss in the substation distribution network and endanger the safety of power grid operation. In this paper, a method of user phase sequence optimization based on historical data is proposed. The historical voltage and current data of users in the distribution network are used to construct the unbalanced power flow model of the distribution network. The objective function of the minimum average voltage imbalance degree of the user node, the minimum line loss and the minimum commutation times in the station area are established according to the operating conditions of the station area within one day. An improved non-dominated sorting genetic algorithm-3(NSGA-3) with a normal distribution crossover (NDX) operator is proposed, and the phase sequence of the user nodes is optimized to obtain a better population distribution and reduce the optimization time. Then the most suitable set of solutions is selected from the solution set as the phase sequence adjustment strategy. Finally, the results validate that the proposed method can effectively reduce the degree of three-phase voltage imbalance and reduce line loss by taking the actual load data of a distribution station area in Anhui Province as an example. © 2023 Power System Protection and Control Press. All rights reserved.

引用

页码：46 / 55

页数：9

共 28 条

[21] AN Youjun, CHEN Xiaohui, Approximate dominance NSGA-III algorithm for solving flexible job-shop scheduling problem, Journal of Systems Engineering, 36, 3, pp. 416-432, (2021)
[22] ZHANG Min, LUO Wenjian, WANG Xufa, A normal distribution crossover for ε-MOEA, Journal of Software, 20, 2, pp. 305-314, (2009)
[23] JIANG Huilan, AN Xing, WANG Yawei, Et al., Improved NSGA2 algorithm based multi-objective planning of power grid with wind farm considering power quality, Proceedings of the CSEE, 35, 21, pp. 5405-5411, (2015)
[24] QIAN Jie, LONG Hongyu, LONG Yi, Et al., Improved NSGA-Ⅲ algorithm and BP fuel-cost prediction network for many-objective optimal power flow problems, IAENG International Journal of Applied Mathematics, (2021)
[25] AI Yongle, DU Mingzhu, PAN Zhihang, Et al., The optimization of reactive power for distribution network with PV generation based on NSGA-III, CPSS Transactions on Power Electronics and Applications, 6, 3, pp. 193-200, (2021)
[26] LI Xiaohui, GAO Duo, YANG Xi, Et al., Application of NSGA-III algorithm based on different dominance relations in robotic cell scheduling problem, Computer Systems & Applications, 31, 2, pp. 279-284, (2022)
[27] AI Jingwen, ZHANG Huaying, WANG Qing, Et al., Study on calculation method of unbalanced factor based on RMS of fundamental current, Electrical Measurement & Instrumentation, 57, 11, pp. 30-36, (2020)
[28] (2008)

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