Quantum-Inspired Evolutionary Algorithm Approach for Unit Commitment

T.W. Lau, C.Y. Chung, Kitpo Wong, T.S. Chung, S.L. Ho

    Research output: Contribution to journalArticle

    107 Citations (Scopus)


    This paper presents a novel method for solving theunit commitment (UC) problem based on quantum-inspired evolutionaryalgorithm (QEA). The proposed method applies QEAto handle the unit-scheduling problem and the Lambda-iterationtechnique to solve the economic dispatch problem. The QEAmethod is based on the concept and principles of quantum computing,such as quantum bits, quantum gates and superposition ofstates. QEA employs quantum bit representation, which has betterpopulation diversity compared with other representations usedin evolutionary algorithms, and uses quantum gate to drive thepopulation towards the best solution. The mechanism of QEA caninherently treat the balance between exploration and exploitationand also achieve better quality of solutions, even with a smallpopulation. The proposed method is applied to systems with thenumber of generating units in the range of 10 to 100 in a 24-hourscheduling horizon and is compared to conventional methods inthe literature. Moreover, the proposed method is extended to solvea large-scale UC problem in which 100 units are scheduled overa seven-day horizon with unit ramp-rate limits considered. Theapplication studies have demonstrated the superior performanceand feasibility of the proposed algorithm.
    Original languageEnglish
    Pages (from-to)1503-1512
    JournalIEEE Transactions on Power Systems
    Issue number3
    Publication statusPublished - 2009

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