Emissions constrained multi-criteria-best generation mix using fuzzy dynamic programming

Jungji Kwon, Jaeseok Choi*, Trungtinh Tran, A. A. El-Keib, Junzo Watada

*Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    9 Citations (Scopus)


    This paper proposes a new approach for solving long-term best generation mix problem considering air pollution constraints (SOχ, NOχ and CO2) and multicriteria under uncertain circumstances by using fuzzy dynamic programming. A characteristic feature of the proposed approach can handle not only fuzziness in fuel and construction cost, load growth, reliability and air pollution but also considering many constraints of best generation mix problems. This approach can accommodate an arbitrary shape of a membership function and the pumped-storage hydro generator operation. The effectiveness of the proposed approach is demonstrated by applying it to solve the multi-years best generation mix problem on the KEPCO-system which contains nuclear, coal, LNG, oil and pumped-storage hydro power plants in Korea.

    Original languageEnglish
    Pages (from-to)41-52
    Number of pages12
    JournalInternational Journal of Innovative Computing, Information and Control
    Issue number1
    Publication statusPublished - 2007 Feb


    • Best generation mix
    • Fuzzy dy-namic programming
    • Gas emission constraints
    • Kyoto Protocol

    ASJC Scopus subject areas

    • Computational Theory and Mathematics
    • Information Systems
    • Software
    • Theoretical Computer Science


    Dive into the research topics of 'Emissions constrained multi-criteria-best generation mix using fuzzy dynamic programming'. Together they form a unique fingerprint.

    Cite this