基于记忆分子动理论多目标优化算法的经济环境调度  

The Economic Environment Dispatch Based on Multi-Objective Memory Kinetic-Molecular Theory Optimization Algorithm

作　　者：李杰 成良江 齐涵 任柯[2] LI Jie;CHENG Liang-jiang;QI Han;REN Ke(State Grid Xiangxiang Power Supply Company,Xiangtan Hunan 411105,China;College of Information and Engineering,Xiangtan University,Xiangtan,Hunan 411105,China)

机构地区：[1]国家电网湖南省电力有限公司湘乡市供电分公司,湖南湘潭411400 [2]湘潭大学信息工程学院,湖南湘潭411105

出　　处：《萍乡学院学报》2018年第6期13-19,共7页Journal of Pingxiang University

基　　金：湖南省研究生科研创新项目(CX2017B339)

摘　　要：针对电力系统经济调度问题的多目标特性,提出一种记忆分子动理论多目标优化算法(Multi-objective MemoryKinetic-MoleculartheoryOptimizationAlgorithm,MOMKMTOA)。该算法在分子动理论算法(Kinetic-Molecular theory Optimization Algorithm, KMTOA)的基础上引入记忆原理记忆,设计记忆更新与遗忘模型以提高算法的多样性,并提出记忆精英选择策略从当代解集中随机选择领导精英以避免陷入局部最优。通过CEC09标准测试函数和IEEE-30节点的两个案例验证说明,MOMKMTOA算法在求解高维复杂的多目标经济调度问题上具有一定的可行性和有效性。Multi-Objective memory Kinetic-Molecular Theory Optimization Algorithm(MOMKMTOA) is proposed to solve the multi-objective characteristics of power system economic dispatching problem.To improve the diversity of the algorithm,the updated operator of memory and the forgotten operator of memory based on Kinetic-Molecular theory Optimization Algorithm(KMTOA) is designed.To avoid falling into local optimum,the selection strategy of leading elite which randomly select the leader from the first-level memory frontier is proposed.Test function of CEC09 and two cases of IEEE-30 nodes show that MOMKMTOA algorithm is feasible and effective in solving multi-objective economic dispatching problems with high-dimensional complexity.

关 键 词：经济环境调度 记忆原理 分子动理论算法 

分 类 号：TM73[电气工程—电力系统及自动化]