Comprehensive Review on Static and Dynamic Distribution Network Reconfiguration Methodologies

Abstract

Reconfiguration of a distribution network is one of the main approaches to control and enhance distribution network indices, such as voltage profile and power losses. Distribution network operators perform reconfiguration for long-term or short-term periods based on network equipment and intended objectives. Long-term or static reconfiguration is suitable for traditional and modern networks with conventional switches. On the other hand, modern distribution networks that are equipped with one or more remote control switches can perform reconfigurations within short-term periods, to maximize predefined objectives. This paper presents a comprehensive review of recent literature on network reconfiguration. Reconfiguration methodologies are classified into five groups: classical methods, heuristic methods, metaheuristic methods, hybrid methods, and methods based on machine learning. The paper provides a general definition and comparison of the categories and discusses their application in dynamic and static reconfiguration. The paper introduces dynamic reconfiguration as the future challenges in smart and modern distribution networks and for the first time categorizes various methodologies in dynamic reconfiguration. The paper serves as a guide to assist engineers and researchers in selecting the most suitable methodology based on their system equipment and objectives.

Keywords

• Distribution network
• optimization
• machine learning
• static reconfiguration
• dynamic reconfiguration
• metaheuristic algorithms