CAJ | 학술논문

在传统的火电厂经济负荷分配模型基础上,综合考虑全厂供电煤耗率、污染物排放量以及全厂负荷升、降时间3个目标,构建了厂级负荷优化分配的多目标模型。将差分粒子群混合算法发展为一种新型的多目标进化(MDPA)算法,即利用擂台赛法和凝聚层次聚类分析方法分别构造和修剪非支配集,同时加入精英保留策略,保留进化过程中的极值点。将该算法应用于以经济、环保、快速3个目标为多目标的厂级负荷优化分配,并与基于非支配排序的多目标优化(NSGA-Ⅱ)算法进行对比。结果表明,MDPA 算法较 NSGA-Ⅱ算法收敛速度更快,解集分布更均匀。
재전통적화전엄경제부하분배모형기출상,종합고필전엄공전매모솔、오염물배방량이급전엄부하승、강시간3개목표,구건료엄급부하우화분배적다목표모형。장차분입자군혼합산법발전위일충신형적다목표진화(MDPA)산법,즉이용뢰태새법화응취층차취류분석방법분별구조화수전비지배집,동시가입정영보류책략,보류진화과정중적겁치점。장해산법응용우이경제、배보、쾌속3개목표위다목표적엄급부하우화분배,병여기우비지배배서적다목표우화(NSGA-Ⅱ)산법진행대비。결과표명,MDPA 산법교 NSGA-Ⅱ산법수렴속도경쾌,해집분포경균균。
On the basis of the conventional single-obj ect model only considering the energy consumption,a multi-obj ective optimization model for load dispatch was established,concerning the energy consumption, environmental protection and load response rate.A hybrid multi-obj ective differential evolution (DE)and particle swarm optimization (PSO)algorithm called MDPA was proposed,which uses arena's principle to establish non-dominate set,cluster analysis to change the size of no-dominate set,elitist strategy to retain extreme points during evolution.Results in three multi-obj ective load dispatch problems show faster con-vergence rate,higher convergence precision and more even distribution of solution set compared with NS-GA-Ⅱ.