A Comprehensive Study of Improved Evolutionary Particle Swarm Optimization (IEPSO) for Network Reconfiguration with DGs Sizing Concurrently

Abstract:

This paper deals with the reconfiguration of the distribution network system to investigate the total power losses considering Distribution Generations (DGs) sizing concurrently. To overcome other limitations and enhance the solution performances, a new optimization approach called Improved Evolutionary Particle Swarm Optimization (IEPSO) is proposed. The primary aim of this study is to investigate the contribution of the proposed algorithms towards total power losses by considering the optimum DG size simultaneously. The proposed method is compared with the traditional Particle Swarm Optimization (PSO) and Improved Particle Swarm Optimization (IPSO) respectively. The amount of time that an algorithm spends in obtaining an alternative topological status for the system power loss reduction and distribution generation sizing is taken into consideration. In this context, the study is tested using IEEE 33 bus distribution system.

• Periodical: Applied Mechanics and Materials (Volume 785)
• Pages: 19-23
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.785.19
• Online since: August 2015
• Authors: Nur Faziera Napis, Mohamad Fani Sulaima*, Aida Fazliana Abd Kadir, Chin Kim Gan, Wardiah Mohd Dahalan, Marizan Sulaiman
• Keywords: Distribution Generation, Distribution Network Reconfiguration, Improved Evolutionary Particle Swarm Optimization

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