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Research Articles

Multi-Objective Distribution Feeder Reconfiguration Considering Reliability in the Presence of Distributed Generators

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Pages 426-442 | Received 25 Oct 2018, Accepted 24 Mar 2020, Published online: 12 Nov 2022
 

Abstract

Improving the efficiency of power systems is a major concern as it provides various benefits including deferment of large investments in substations and generation. In this regard, the distribution feeder reconfiguration (DFR) can help reduce system losses by changing the status of switches. In solving the DFR problem, power loss and voltage deviation of buses are commonly considered objective functions, but less attention has been paid to the reliability indexes as objective functions. In this study, DFR is solved as a multi-objective problem using the proposed reliability index along with power loss and switching number in the presence of distributed generators. A powerful hybrid algorithm based on the combination of particle swarm optimization and modified shuffled frog leaping is proposed to solve the DFR problem. To evaluate the efficiency of the proposed hybrid algorithm, two 33-bus and 70-bus systems are tested.

Additional information

Notes on contributors

Hossein Lotfi

Hossein Lotfi received B.Sc. and M.Sc. degrees from Islamic Azad University of Bojnourd, in 2010 and 2013. In 2019 he received his degree from Islamic Azad University of Neyshabur, all in electrical engineering. He is currently Post-doctoral researcher in Hakim Sabzevari university. His main research interests are renewable energy sources, power system reliability and stability and evolutionary algorithms.

Reza Ghazi

Reza Ghazi received the M.Sc. degree from Manchester University, Institute of Science and Technology (UMIST), in 1986. In 1989 he received his Ph.D. degree from University of Salford UK, all in electrical engineering. He is currently Professor of Electrical Engineering in Ferdowsi University of Mashhad, Mashhad, Iran. His main research interests are reactive power control, FACTS devices, and distributed generation.

Mohammad Bagher Naghibi Sistani

Mohammad Bagher Naghibi Sistani received the B.Sc. and M.Sc. degrees in control engineering from the University of Tehran, Tehran, Iran, in 1991 and 1995, respectively, and the Ph.D. degree from the Department of Electrical Engineering, Ferdowsi University of Mashhad, Mashhad, Iran, in 2005. From 2001 to 2005, he was a Lecturer at the Ferdowsi University of Mashhad, where he is currently an Assistant Professor. His current research interests include artificial intelligence, reinforcement learning, and control systems.

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