Fast solution technique for large-scale unit commitment problem using genetic algorithm
Fast solution technique for large-scale unit commitment problem using genetic algorithm
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DOI：
10.1049/ip-gtd:20030939
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发表时间：
2003-11
期刊：
影响因子：
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通讯作者：
T. Senjyu;H. Yamashiro;K. Shimabukuro;K. Uezato;T. Funabashi
中科院分区：
文献类型：
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作者：
T. Senjyu;H. Yamashiro;K. Shimabukuro;K. Uezato;T. Funabashi
提出了一种求解大规模机组组合问题的方法。机组组合问题是电力系统中的一个重要问题，改善机组组合计划可以降低运行成本。然而，机组组合问题是电力系统中最困难的优化问题之一，因为这个问题有很多约束条件。此外，搜索空间很大。针对这些问题，提出了一种基于单元特征分类和单元集成技术的遗传算子。所提出的算法进行了测试报告UC问题。从模拟结果中，得到更好的解决方案与以前报道的结果相比。系统的数值结果高达100个单位相比，以前报道的结果。
An approach for a large-scale unit commitment problem is presented. The unit commitment (UC) problem plays a major role in power systems, because the improvement of commitment schedules results in the reduction of operating costs. However, the unit commitment problem is one of the most difficult optimisation problems in power systems, because this problem has many constraints. Moreover, search space is vast. To overcome these problems, a new genetic operator based on unit characteristic classification and unit integration technique are proposed. The proposed algorithm was tested on a reported UC problem. From simulation results, better solutions are obtained in comparison with previously reported results. Numerical results for systems up to 100 units are compared to previously reported results.