| Summary: | 碩士 === 義守大學 === 電機工程學系碩士班 === 97 === The objective of unit commitment is to schedule the status and the real power outputs of units and minimize the system production cost during the period while simultaneously satisfying the load demand, spinning reserve, physical and operational constraints of the individual unit.
Nevertheless, unit commitment is a optimization problem in essence. That is, when the global optimal solution is available for the problem itself, it requires a great deal of time on computation efforts. In this thesis, the Parallel Genetic Algorithm approaches are presented to solve the unit commitment problem, and comparison with the results obtained using Genetic Algorithm. The approaches are introduced in this thesis since they are based on the principle of natural selection and survival of the fittest, which require computational explosion to obtain the global optimal solution for huge number of crossover, mutation, and judgment amount their combination. Fortunately, the specialty of being high efficient with parallel computation on PC cluster, the time-consuming problem can be solved.
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