Power Distribution Network Reconfiguration Techniques: A Thorough Review

Hossein Lotfi (), Mohammad Ebrahim Hajiabadi and Hossein Parsadust
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Hossein Lotfi: Department of Electrical and Computer Engineering, Hakim Sabzevari University, Sabzevar 96131, Iran
Mohammad Ebrahim Hajiabadi: Department of Electrical and Computer Engineering, Hakim Sabzevari University, Sabzevar 96131, Iran
Hossein Parsadust: Department of Electrical and Computer Engineering, Hakim Sabzevari University, Sabzevar 96131, Iran

Sustainability, 2024, vol. 16, issue 23, 1-33

Abstract: Distribution network reconfiguration (DNR) plays a vital role in enhancing network sustainability by optimizing its topology. This process achieves key objectives such as reducing power losses, improving voltage profiles, balancing loads, and increasing network reliability, aligning with sustainability metrics. Depending on the goals and equipment available, reconfiguration may be applied for short-term or long-term durations. Long-term or static reconfiguration suits both conventional switches and traditional as well as modern networks. In modern networks equipped with remote-control switches, however, reconfiguration can be implemented rapidly to meet specific operational objectives. This study provides a comprehensive review of recent advancements in network reconfiguration, categorizing methods into four groups: heuristic, metaheuristic, conventional, and modern approaches. Each category is broadly defined and compared, with applications discussed for both static and dynamic reconfiguration. Dynamic reconfiguration is highlighted as a key area for future exploration in smart and modern distribution networks. This article serves as a resource for engineers and researchers, helping them select the most suitable method based on network equipment and performance goals.

Keywords: distribution network; static reconfiguration; dynamic reconfiguration; optimization methos; power loss; sustainability (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
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