Radial distribution network reconfiguration for power losses reduction using a modified particle swarm optimisation

Inji Atteya, H.A. Ashour, Nagi R Fahmi, Danielle R Strickland

Research output: Contribution to journalArticlepeer-review


Abstract: Recently, losses reduction gained a great deal of attention in distribution system due to low-voltage level and the high-current passing through the lines, pushing the distribution utilities to improve their profit margins on one hand by reducing the unnecessary operational cost, and improving their delivered power quality on the other hand by
maintaining the system reliability, and the continuity of supply for varying load demand. Load balancing, voltage regulation, network reconfiguration and others are different techniques used to reduce the losses. This study addresses the distribution network reconfiguration to minimise the network losses. A new modified form of particle swarm optimisation (PSO) is used to identify the optimal configuration of distribution network effectively. The difference
between the modified PSO (MPSO) algorithms and the typical one is the filtered random selective search space for initial position, which is proposed to accelerate the algorithm for reaching the optimum solution. The suggested MPSO is tested via 33 and 69 IEEE networks. A benchmark comparison has been conducted to prove the effectiveness of MPSO compared with previous optimisation techniques.
Original languageEnglish
Pages (from-to)2505 - 2508
Number of pages4
JournalIET Networks
Early online date1 Oct 2017
Publication statusPublished - 1 Oct 2017
Event24th International Conference & Exhibition on Electricity Distribution (CIRED) - Glasgow, United Kingdom
Duration: 12 Jun 201715 Jun 2017

Bibliographical note

This is an open access article published by the IET under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/).


  • voltage control
  • power supply quality
  • profitability
  • search problems
  • power distribution economics
  • minimisation
  • power distribution reliability
  • particle swarm optimisation


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