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山东大学学报(工学版) ›› 2018, Vol. 48 ›› Issue (4): 1-9.doi: 10.6040/j.issn.1672-3961.0.2017.369

• 机器学习与数据挖掘 •    下一篇

计及排放的动态经济调度免疫克隆演化算法

钱淑渠1,武慧虹1,徐国峰2,金晶亮3   

  1. 1. 安顺学院数理学院, 贵州 安顺 561000;2. 南京工程学院计算中心, 江苏 南京 210016;3. 南通大学理学院, 江苏 南通 226000
  • 收稿日期:2017-05-20 出版日期:2018-08-20 发布日期:2017-05-20
  • 作者简介:钱淑渠(1978— ), 男, 安徽枞阳人, 副教授, 工学博士, 主要研究方向为计算智能,系统建模与控制. E-mail:shuquqian@163.com
  • 基金资助:
    国家自然科学基金资助项目(61762001,71603135);贵州省科学技术基金资助项目(黔科合J字［2015］2002,黔科合LH字［2017］7047);贵州省教育厅优秀科技创新人才奖励计划资助项目(黔教合KY字［2014］255);南京工程学院创新基金面上资助项目II(CKJC201603);江苏省高校创新基金资助项目(KYLX15-0274)

Immune clonal evolutionary algorithm of dynamic economic dispatch considering gas pollution emission

QIAN Shuqu1, WU Huihong1, XU Guofeng2, JIN Jingliang3   

  1. 1. School of Sciences, Anshun University, Anshun 561000, Guizhou, China;
    2. Computing Center, University of Engineering of Nanjing, Nanjing 210016, Jiangsu, China;
    3. School of Sciences, Nantong University, Nantong 226000, Jiangsu, China
  • Received:2017-05-20 Online:2018-08-20 Published:2017-05-20

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摘要： 结合免疫系统的克隆选择原理和遗传进化机制,提出一种免疫克隆演化算法(Immune clonal evolutionary algorithm, ICEA)。ICEA建立克隆选择机制与演化机制的动态结合,提出动态免疫选择和自适应非均匀突变算子,针对动态经济调度(dynamic emission economic dispatch, DEED)问题特性引入不同的等式和不等式的约束修补策略,使其适合大规模约束的DEED问题求解。数值试验将ICEA应用于10机系统进行测试,并与同类算法展开比较。仿真结果表明,ICEA具有较好的收敛性和全局优化效果,获得的Pareto前沿具有较好的均匀性和延展性,该结果能为电力系统调度人员提供较为有效的调度决策方案。

关键词: 动态免疫选择, 进化优化, 动态经济调度, 约束多目标优化, 自适应

Abstract: An immune clonal evolutionary algorithm(ICEA)was proposed by combining the clone selection principle of immune system and the evolution mechanism of genetic algorithm. A kind of dynamic immune selection strategy was introduced and a self-adaption non-uniform mutation operator was proposed. In order to make it suitable for solving dynamic emission economic dispatch(DEED)problem with many constrains, different repair strategies were introduced for the equality and inequality constrains of DEED model. In numerical experiments, ICEAs performance on 10-units system was tested, and several peer algorithms were compared. The simulation results indicated that ICEA had good convergence and global optimization efficiency. The uniformity and ductility of the Pareto optimal frontier obtained by ICEA was better than that of comparison algorithms. The Pareto optimal frontier could provide a more efficient scheduling decision-making approach for power system dispatcher.

Key words: evolution optimization, constrained multiobjective optimization, dynamic immune selection, self-adaption, dynamic economic dispatch

中图分类号: 

  • TP306.1
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