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 journalArticlepeer-review

    73 Citations (Scopus)

    Abstract

    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
    Volume18
    Issue number3
    DOIs
    Publication statusPublished - 2008 Apr

    Keywords

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

    ASJC Scopus subject areas

    • Energy Engineering and Power Technology
    • Electrical and Electronic Engineering

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