Multiobjective distributed generation placement using fuzzy goal programming with genetic algorithm

Kyu Ho Kim, Kyung Bin Song, Sung-Kwan Joo, Yu Jeong Lee, Jin O. Kim

Research output: Contribution to journalArticle

62 Citations (Scopus)


This paper presents a new method to determine the locations and sizes of Distributed Generations (DGs) for loss reduction and voltage profile enhancement in distribution systems. The strategic placement of DG can help reduce power losses and improve feeder voltage profile. Fuzzy Goal Programming (FGP) is adopted to handle the multiobjective DG placement problem incorporating the voltage characteristics of each individual load component. The original objective functions and constraints are transformed into the multiobjective function with fuzzy sets by FGP. The transformed multiobjective function with fuzzy sets represents the imprecise natures for criterion of loss reduction and voltage profile enhancement, and the number and total capacities of DGs. The solution of the transformed multiobjective function with fuzzy sets is searched by Genetic Algorithm (GA). The proposed method is tested on the IEEE 34-bus system to demonstrate its effectiveness.

Original languageEnglish
Pages (from-to)217-230
Number of pages14
JournalEuropean Transactions on Electrical Power
Issue number3
Publication statusPublished - 2008 Apr 1



  • Distributed Generation (DG)
  • Fuzzy Goal Programming (FGP)
  • Genetic Algorithm (GA)

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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