JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE) ›› 2018, Vol. 48 ›› Issue (4): 1-9.doi: 10.6040/j.issn.1672-3961.0.2017.369

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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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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

CLC Number: 

  • TP306.1
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