Journal of Computer Applications ›› 2015, Vol. 35 ›› Issue (8): 2249-2255.DOI: 10.11772/j.issn.1001-9081.2015.08.2249

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Constrained multiobjective optimization algorithm based on repairing strategy for solving dynamic environment/economic dispatch

QIAN Shuqu1, WU Huihong1, XU Guofeng2   

  1. 1. School of Sciences, Anshun University, Anshun Guizhou 561000, China;
    2. Industrial Center, Nanjing Institute of Technology, Nanjing Jiangsu 210016, China
  • Received:2015-02-12 Revised:2015-03-25 Online:2015-08-10 Published:2015-08-14


钱淑渠1, 武慧虹1, 徐国峰2   

  1. 1. 安顺学院 数理学院, 贵州 安顺 561000;
    2. 南京工程学院 工业中心, 南京 210016
  • 通讯作者: 钱淑渠(1978-),男,安徽枞阳人,副教授,博士研究生,主要研究方向:智能计算、系统建模及控制,
  • 作者简介:武慧虹(1980-),女,山西太原人,副教授,硕士,主要研究方向:优化算法、群与图; 徐国峰(1976-),男,湖北武穴人,讲师,主要研究方向:重复控制、电力电子。
  • 基金资助:



The classical multiobjectve optimization algorithm is difficult to achieve high quality feasible solutions on Multiobjectve Dynamic Environment/Economic Dispatch (MODEED) model, and shows a slower convergence speed. Firstly, a new constraint repairing strategy based on the constraint characteristic of MODEED was developed. Secondly, the proposed repairing approach was inserted into the Nondominated Sorting Genetic Algorithm-Ⅱ (NSGAⅡ), and a Constrained Multiobjective Evolutionary Algorithm based on repairing Strategy (CMEA/R) was proposed. Thirdly, fuzzy decision theory was applied to determine the best compromise solution of the MODEED. Finally, to validate the optimization ability of the CMEA/R, it was applied to solve the MODEED problem of standard IEEE 30-bus 10-generator system, and a comparative analysis with NSGAⅡ was presented under various population size. The simulation results revealed that the pollutant emission and fuel cost obtained by CMEA/R were reduced by 480 lb (217.7 kg) and 7 800 dollar, respectively, the average implication time was reduced by 0.021 second. Furthermore, CMEA/R shows a superior performance in terms of Hypervolume Rate (HR) indicator and convergence ability.

Key words: power system, dynamic environment/economic dispatch, multiobjective optimization, repairing strategy, convergence


针对传统的优化算法求解多目标动态环境经济调度(MODEED)模型时极难获得高质量的可行解,且收敛速度慢等问题,根据MODEED模型约束特征,设计了一种约束修补策略;然后将该策略嵌入非支配排序算法(NSGAⅡ),进而提出一种修补策略的约束多目标优化算法(CMEA/R);接着借助模糊决策理论给出了多目标问题的最优决策向量;最后,以经典的10机系统为例,验证了CMEA/R的求解能力,并比较了不同群体规模下CMEA/R与NSGAⅡ的性能。仿真结果表明,在不同群体规模下,与NSGAⅡ相比,CMEA/R的污染排放平均减少了480 lb(217.7 kg),燃料成本平均减少了7 800美元,执行时间平均减少了0.021 s;覆盖率(HR)性能优于NSGAⅡ,且收敛速度较NSGAⅡ快。

关键词: 电力系统, 动态环境经济调度, 多目标优化, 修补策略, 收敛性

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