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2013 (Vol. 5, Issue: 20)
Article Information:

Application of Particle Swarm Optimization for Optimal Distributed Generation Allocation to Voltage Profile Improvement and Line Losses Reduction in Distribution Network

Mohammad Shahab Arkan and Hamed Salehi
Corresponding Author:  Mohammad Shahab Arkan 

Key words:  DG allocation, distributed generation, loss reduction, particle swarm optimization, voltage profile, ,
Vol. 5 , (20): 4791-4795
Submitted Accepted Published
January, 19, 2012 May 18, 2012 May 15, 2013
Abstract:

Distributed Generation (DG) had created a challenge and an opportunity for developing various novel technologies in power generation. The rate and size of DG implementation have o be determined. The increasing need of electricity and establishing powerhouses, as well as to spend a great amount of time to build powerhouses, indicate the necessity of distributed generation in small size and close to the consumer location. In this study, selecting a part of Tehran network, attempts to investigate the effects of distributed generation on line losses and voltage profile using PSO. The introduction of PSO based DG in a distribution system offers several benefits: Significant voltage profile improvement, Considerable line loss reduction, Improves system reliability and etc. The optimum value of the DG, also obtained increases the maximum load ability of the system. The proposed method is tested on a system and the results of the simulation carried out will be given. Finally the results are compared to system without installation DG. The method has a potential to be a tool for identifying the best location and rating a DG to be installed for improving voltage profile and reduce losses.
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  Cite this Reference:
Mohammad Shahab Arkan and Hamed Salehi, 2013. Application of Particle Swarm Optimization for Optimal Distributed Generation Allocation to Voltage Profile Improvement and Line Losses Reduction in Distribution Network.  Research Journal of Applied Sciences, Engineering and Technology, 5(20): 4791-4795.
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ISSN (Online):  2040-7467
ISSN (Print):   2040-7459
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