Research on Optimal Load Distribution of Power Plants Based on Chaos Genetic Algorithm

Hao Yang, Yongguang Ma, Sihan Chen, Fuyu Qiao
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Abstract

According to the structural characteristics of chaotic motion, chaotic variables are introduced into the genetic algorithm optimization process, so that the values of the two are mapped to each other, and the group that adds chaotic disturbances is selected according to the fitness level, and the guidance of mutation operation is increased. Chaos is proposed Genetic algorithm. This improved algorithm is applied to the optimal distribution of plant-level load in power plants, and the coal consumption of thermal power plants is verified by simulation experiments. The results show that this algorithm can obtain better optimization results in the plant-level load optimization distribution problem, allowing the power plant to obtain better economy.
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基于混沌遗传算法的电厂负荷优化分配研究
根据混沌运动的结构特点,在遗传算法优化过程中引入混沌变量,使两者的值相互映射,并根据适应度选择添加混沌扰动的组,增加突变操作的指导作用。提出了混沌遗传算法。将该改进算法应用于电厂厂级负荷优化分配,并通过仿真实验对火电厂的煤耗进行了验证。结果表明,该算法在电厂级负荷优化分配问题中能够获得较好的优化结果,使电厂获得较好的经济性。
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