Improved tunicate swarm algorithm: solving the dynamic economic emission dispatch problems

Ling-Ling Li, Zhi-Feng Liu, Ming-Lang Tseng, Sheng-Jie Zheng, Ming Lim

    Research output: Contribution to journalArticlepeer-review

    107 Citations (Scopus)
    104 Downloads (Pure)

    Abstract

    This study proposes improved tunicate swarm algorithm (ITSA) for solving and optimizing the dynamic economic emission dispatch (DEED) problem. The DEED optimization target is to reduce the fuel cost and pollutant emission of the power system. In addition, DEED is a complex optimization problem and contains multiple optimization goals. To strengthen the ability of the ITSA algorithm for solving DEED, the tent mapping is employed to generate initial population for improving the directionality in the optimization process. Meanwhile, the gray wolf optimizer is used to generate the global search vector for improving global exploration ability, and the Levy flight is introduced to expand the search range. Three test systems containing 5, 10 and 15 generator units are employed to verify the solving performance of ITSA. The test results show that the ITSA algorithm can provide a competitive scheduling plan for test systems containing different units. ITSA proposed algorithm gives the optimal economic and environmental dynamic dispatch scheme for achieving more precise dispatch strategy.
    Original languageEnglish
    Article number107504
    JournalApplied Soft Computing
    Volume108
    Early online date19 May 2021
    DOIs
    Publication statusPublished - Sept 2021

    Funder

    This study was supported by the key project of Tianjin Natural Science Foundation, China [Project No. 19JCZDJC32100] and the Natural Science Foundation of Hebei Province of China [Project No. E2018202282].

    Keywords

    • Dynamic economic emission dispatch
    • Fuel cost
    • Improved tunicate swarm algorithm
    • Power system
    • Soft-computing

    ASJC Scopus subject areas

    • Software

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