Journal of Shandong University(Engineering Science) ›› 2021, Vol. 51 ›› Issue (1): 11-23.doi: 10.6040/j.issn.1672-3961.0.2020.050

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Multiobjective dynamic economic emission dispatch differential evolution algorithm based on elites cloning local search

WU Huihong1, QIAN Shuqu1*, LIU Yanmin2, XU Guofeng3, GUO Benhua1   

  1. 1. School of Mathematics and Physics, Anshun University, Anshun 561000, Guizhou, China;
    2. School of Mathematics, Zunyi Normal University, Zunyi 563006, Guizhou, China;
    3. Computing Center, Nanjing Institute of Technology, Nanjing 211167, Jiangsu, China
  • Published:2021-03-01

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Abstract: An efficient multiobjective differential evolution algorithm based on elites cloning local search scheme was proposed to solve complex dynamic economic emission dispatch. The conventional differential evolution(DE)algorithm was used as the framework of the proposed algorithm. A cloning operator was developed to enhance the exploration and exploitation ability of elites in the DE algorithm. The elite population to be cloned was established by a dynamic selection mechanism for enhancing the global search ability of the proposed algorithm. To validate the effectiveness of the proposed algorithm, the IEEE 30 bus 10-generator and 15-generator systems were studies as test cases in numerical experiments. The simulation results indicated that the Pareto-optimal front obtained by the proposed algorithm presented a superior performance in convergence and extension over the other reported results recently. As a result, the results were able to provide decision solutions more extensively for decision-makers in power system dispatch.

Key words: dynamic economic emission dispatch, multiobjective optimization, elites cloning, differential evolution, Pareto-optimal front

CLC Number: 

  • TP306.2
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