[1]高山,单渊达.遗传算法在机组启停中的应用及改进[J].东南大学学报(自然科学版),2000,30(3):51-57.[doi:10.3969/j.issn.1001-0505.2000.03.011] 　Gao Shan,Shan Yuanda.Advanced Genetic Algorithm Approach to Unit Commitment[J].Journal of Southeast University (Natural Science Edition),2000,30(3):51-57.[doi:10.3969/j.issn.1001-0505.2000.03.011] 点击复制 遗传算法在机组启停中的应用及改进() 分享到： var jiathis_config = { data_track_clickback: true };

30

2000年第3期

51-57

2000-05-20

文章信息/Info

Title:
Advanced Genetic Algorithm Approach to Unit Commitment

Author(s):
Department of Electrical Engineering, Southeast University, Nanjing 210096

Keywords:

TM731
DOI:
10.3969/j.issn.1001-0505.2000.03.011

Abstract:
This paper discusses an advanced application of genetic algorithm to determine the short-term unit commitment. Some heuristic techniques are developed. First, the method to create initial generation, every unit in the initial generation is a feasible solution of unit commitment. Second, feasibility checking method builds a relation between infeasible solution space and feasible solution space, reduces lots of invalid processes in genetic searching. Third, redundancy-checking method reduces the redundancies of some solutions whose redundancies are too big. Fourth, a boundary searching method can easily get a better solution from a feasible unit. As a result the genetic algorithm used in short-term unit commitment is greatly enhanced.

参考文献/References:

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