Application of a new hybrid optimization method for optimum distribution capacitor planning

A. R. Seifi, M. R. Hesamzadeh, N. Hosseinzadeh, P. Wolfs

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

This work presents a new algorithm based on a combination of fuzzy (FUZ), Dynamic Programming (DP), and Genetic Algorithm (GA) approach for capacitor allocation in distribution feeders. The problem formulation considers two distinct objectives related to total cost of power loss and total cost of capacitors including the purchase and installation costs. The novel formulation is a multi-objective and non-differentiable optimization problem. The proposed method of this article uses fuzzy reasoning for sitting of capacitors in radial distribution feeders, DP for sizing and finally GA for finding the optimum shape of membership functions which are used in fuzzy reasoning stage. The proposed method has been implemented in a software package and its effectiveness has been verified through a 9-bus radial distribution feeder for the sake of conclusions supports. A comparison has been done among the proposed method of this paper and similar methods in other research works that shows the effectiveness of the proposed method of this paper for solving optimum capacitor planning problem.

Original languageEnglish
Title of host publication8th International Power Engineering Conference, IPEC 2007
Pages70-74
Number of pages5
Publication statusPublished - 2007
Externally publishedYes
Event8th International Power Engineering Conference, IPEC 2007 - Singapore, Singapore
Duration: Dec 3 2007Dec 6 2007

Publication series

Name8th International Power Engineering Conference, IPEC 2007

Other

Other8th International Power Engineering Conference, IPEC 2007
Country/TerritorySingapore
CitySingapore
Period12/3/0712/6/07

Keywords

  • Capacitor planning
  • Dynamic Programming
  • Fuzzy logic method
  • Genetic algorithm
  • Radial distribution feeder

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering

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