Open Access

REVIEW

A Critical Review of Active Distribution Network Reconfiguration: Concepts, Development, and Perspectives

Bo Yang¹, Rui Zhang¹, Jie Zhang², Xianlong Cheng², Jiale Li³, Yimin Zhou¹, Yuanweiji Hu¹, Bin He¹, Gongshuai Zhang⁴, Xiuping Du⁴, Si Ji⁵, Yiyan Sang⁶, Zhengxun Guo^7,8,*

1 Faculty of Electric Power Engineering, Kunming University of Science and Technology, Kunming, 650500, China
2China Southern Power Grid Honghe Power Supply Bureau, Mengzi, 661100, China
3 Faculty of Science, Kunming University of Science and Technology, Kunming, 650500, China
4China Southern Power Grid Yuxi Power Supply Bureau, Yuxi, 653100, China
5 Yunnan Electric Power Grid Co., Ltd., Kunming, 650000, China
6 College of Electrical Engineering, Shanghai University of Electric Power, Shanghai, 200090, China
7 College of Information Science and Engineering, Northeastern University, Shenyang, 110819, China
8 Foshan Graduate School of Innovation, Northeastern University, Foshan, 528311, China

* Corresponding Author: Zhengxun Guo. Email:

Energy Engineering 2024, 121(12), 3487-3547. https://doi.org/10.32604/ee.2024.054662

Received 04 June 2024; Accepted 02 September 2024; Issue published 22 November 2024

Abstract

In recent years, the large-scale grid connection of various distributed power sources has made the planning and operation of distribution grids increasingly complex. Consequently, a large number of active distribution network reconfiguration techniques have emerged to reduce system losses, improve system safety, and enhance power quality via switching switches to change the system topology while ensuring the radial structure of the network. While scholars have previously reviewed these methods, they all have obvious shortcomings, such as a lack of systematic integration of methods, vague classification, lack of constructive suggestions for future study, etc. Therefore, this paper attempts to provide a comprehensive and profound review of 52 methods and applications of active distribution network reconfiguration through systematic method classification and enumeration. Specifically, these methods are classified into five categories, i.e., traditional methods, mathematical methods, meta-heuristic algorithms, machine learning methods, and hybrid methods. A thorough comparison of the various methods is also scored in terms of their practicality, complexity, number of switching actions, performance improvement, advantages, and disadvantages. Finally, four summaries and four future research prospects are presented. In summary, this paper aims to provide an up-to-date and well-rounded manual for subsequent researchers and scholars engaged in related fields.

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Keywords

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