基于非支配排序遗传算法的无约束多目标优化配煤模型  

A Model of Unconstrained Multi-objective Optimization of Coal Blending Based on the Non-dominated Sorting Genetic Algorithm

作　　者：夏季[1] 华志刚[1] 彭鹏[1] 陆潘[1] 张成[1] 陈刚[1] 

机构地区：[1]煤燃烧国家重点实验室(华中科技大学),湖北省武汉市430074

出　　处：《中国电机工程学报》2011年第2期85-90,共6页Proceedings of the CSEE

基　　金：国家自然科学基金项目(50721005);广东省重大科技专项项目资助(2008A080800029)~~

摘　　要：分析单目标动力配煤模型的缺点,提出多目标优化配煤模型,模型将所有煤质指标都作为优化目标,根据每个指标的特点构建出安全性、经济性和环保性3个目标函数。引入带有精英策略的非支配排序遗传算法(non-dominated sorting genetic algorithm,NSGA-II)作为该模型的寻优算法,并结合配煤问题的特点对原算法进行适当改进和调整,对某电厂的实际配煤问题进行求解,得到分布较好的Pareto最优解集,这些解为电厂配煤人员在多个相互关联的目标之间进行决策时提供了多样的选择,具有很好的指导作用和应用价值。To overcome the shortcomings of single-objective optimization model for coal blending,a multi-objective optimization model which all the coal quality indicators were considered as optimum targets was established.According to the characteristics of each indicator,three objective functions were built to reflect the security,economical and environmental requirements of coal blending.As a good multi-objective optimization algorithm,non-dominated sorting genetic algorithm（NSGA-II） with some appropriate improvements was used to gain the optimum solution.This method was applied in a multi-objective coal blending problem of a real power plant,and well-distributed Pareto-optimal solutions were obtained.These blending solutions can provide a variety of options for the power plant personnel in a number of interrelated decision-making between the objectives.

关 键 词：火电厂 配煤 多目标优化 非支配排序遗传算法 

分 类 号：TK121[动力工程及工程热物理—工程热物理]