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Unit commitment problems using GA

机译:使用GA的单位承诺问题

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摘要

In this paper, Unit Commitment (UC) using the generic algorithm (GA) with different implementary techniques, such as different sampling space methods, different selection schemes, different fitness value scaling methods and different crossover/mutation rates, is developed and implemented in 10 units system and 110 units system. This paper thoroughly studies the effects on convergent time, convergent generation number and convergent value of GA based on different implementary techniques, which indicates that the algorithm is effective in a certain degree, and reveals that different implementary techniques have different effects on convergent time, convergent generation number, and convergent value of GA-based UC. A good foundation is settled for further practicable study of GA-based UC.
机译:在本文中,单位承诺(UC)使用具有不同实现技术的通用算法(GA),例如不同的采样空间方法,不同的选择方案,不同的健身值缩放方法和不同的交叉/突变率,并在10中实现和实现单位系统和110个单元系统。本文彻底研究了基于不同的实现技术对GA的收敛时间,收敛生成数量和会聚值的影响,这表明该算法在一定程度上有效,并揭示了不同的实施技术对收敛时间有不同的影响,会聚基于GA的UC的生成编号和收敛价值。良好的基础是对基于GA的UC的进一步切实可行研究。

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