Novel Particle Swarm Optimization approach for multi objective planning of power distribution network under load uncertainty

Journal Title: International Research Journal of Applied and Basic Sciences - Year 2012, Vol 3, Issue 12

Abstract

In this paper, static and expansion planning of electric power distribution networks were studied using a novel Particle Swarm Optimization (PSO) algorithm under load uncertainty is presented. This paper consists of two sections. At first by using a novel PSO algorithm, static and mono objective planning was solved for electric distribution network. This work involves both network topology and size of branches’ conductor. In these stage uncertainties is ignored. The purpose of this stage studying effectiveness of PSO algorithm in distribution networks planning. In the next stage expansion and multi objective planning for electric distribution networks is presented those uncertainties as the important parameters in design distribution network design are considered. Two main objectives in multi objective planning are reduction real power loss cost and improve network reliability (with reduce total non-delivered energy). Finally in order to selection best network (lossless and reliable) a criterion namely Infeasibility Rate (IR) of network is used. To show the effectiveness of the proposed algorithm, simulations were carried out on standard distribution systems (21 and 23 bus).

Authors and Affiliations

Rasoul Mohammadi tab| University of Mohaghegh Ardabili, Ardabil, Iran,r.mohammaditab@gmail.com, Seyed-Jalal Seyed-Shenava| University of Mohaghegh Ardabili, Ardabil, Iran, Khalil Valipour| University of Mohaghegh Ardabili, Ardabil, Iran

Keywords

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  • EP ID EP5199
  • DOI -
  • Views 397
  • Downloads 18

How To Cite

Rasoul Mohammadi tab, Seyed-Jalal Seyed-Shenava, Khalil Valipour (2012). Novel Particle Swarm Optimization approach for multi objective planning of power distribution network under load uncertainty. International Research Journal of Applied and Basic Sciences, 3(12), 2408-2419. https://europub.co.uk/articles/-A-5199