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Title: Distribution network reconfiguration in smart grid system using modified particle swarm optimization
Authors: Atteya, I.I.
Ashour, H.A.
Fahmi, N.
Strickland, Dani
Keywords: Smart grid
Distribution system
Distributed network reconfiguration
Modified particle swarm optimization
Issue Date: 2017
Publisher: © IEEE
Citation: ATTEYA, I.I. ... et al, 2017. Distribution network reconfiguration in smart grid system using modified particle swarm optimization. Presented at the IEEE 5th International Conference on Renewable Energy Research and Applications, (ICRERA) 2016, Birmingham, UK, 20th-23rd November 2016, pp. 305-313.
Abstract: One of the major characteristic of a smart protection system in Smart grid is to automatically reconfigure the network for operational conditions improvement or during emergency situations avoiding outage on one hand and ensuring power system reliability the other hand. This paper proposes a modified form of particle swarm optimization to identify the optimal configuration of distribution network effectively. The difference between the Modified Particle Swarm Optimization algorithms (MPSO) 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 main objective function is to minimize the power losses as it represents high waste of operational cost. The suggested method is tested on a 33 IEEE network using IPSA software. Results are compared to studies using other forms of swarm optimization algorithms such as the typical PSO and Binary PSO. 29% of losses reduction has been achieved during a less computational time.
Description: © IEEE 2016. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Version: Accepted for publication
DOI: 10.1109/ICRERA.2016.7884556
URI: https://dspace.lboro.ac.uk/2134/25185
Publisher Link: http://dx.doi.org/10.1109/ICRERA.2016.7884556
ISBN: 9781509033881
Appears in Collections:Conference Papers and Presentations (Mechanical, Electrical and Manufacturing Engineering)

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