机组负荷分配的多目标优化和多属性决策

同时计及机组运行的经济性和污染排放,将基于进化算法的多目标优化技术与多属性决策方法联合运用,针对火电厂负荷优化分配问题进行了研究。对于多目标优化问题,采用改进的非支配解排序的多目标遗传算法(NSGAⅡ),求出Pareto最优解,由这些Pareto最优解构成决策矩阵,使用客观赋权的信息熵方法对最优解的属性进行权值计算,然后用逼近理想解的排序方法(TOPSIS)进行多属性决策(MADM)研究,对Pa-reto最优解给出排序。给出了3台机组负荷分配的优化算例,计算表明所提方法适应性好,结果合理可行。

Multi-Objective Optimization and Multi-Attribute Decision Making Analysis for Economic Load Dispatch

According to operation economy and pollution emission,optimization load dispatch is analyzed based on multi-objective optimization method and multi-attribute decision making algorithm.In the problem of multi-objective optimization,Pareto optimal solutions are solved with improved non-dominated sorting genetic algorithmⅡ(NSGAⅡ).These pareto optimal solutions compose decision matrix.The weights of optimal solutions attribute are calculated with information entropy,and then a multi-attribute decision making(MADM)approach is adopted to rank these solutions from best to worst based on technique for order preference by similarity to ideal solution(TOPSIS).An optimal example of 3-unit system is presented.The results show that the proposed approach has better adaptability and feasibility.