Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 40, 2023 No. 9
2720-2728

Hybrid immune multi-objective optimization algorithm for dynamic emission economic dispatch

Tang Xiangqian1,2
Qian Shuqu2
Wu Huihong2
1. College of Mathematics & Statistics, Guizhou University, Guiyang 550025, China
2. School of Mathematics & Computer Sciences, Anshun University, Anshun Guizhou 561000, China
DOI: 10.19734/j.issn.1001-3695.2023.02.0037

Abstract

Dynamic economic emission dispatch(DEED) problem in power system is a kind of high-dimensional multi-objective optimization problem with large-scale constraints. The traditional evolutionary algorithm is easy to fall into local optimization, and the distribution and convergence of the obtained Pareto frontier are poor. This paper fully explored the clonal selection principle of immune system, and proposed a hybrid immune multi-objective optimization algorithm(HIMOA). The proposed algorithm took the traditional evolutionary algorithm as the basic framework. Since the deficiency of falling local optimization for the high-dimensional decision variables optimization, it improved the external archive update mechanism to preserve the excellent individuals from previous generations, and adopted the cloning and Gaussian mutation strategy to strengthen the local exploitation ability, forcing effectively the HIMOA to jump out of the stagnant search state. In order to cope with the large-scale constraints, it designed the fine-turning output power step by step to improve the feasibility of the evolutionary population. In the numerical simulation experiment, taking a 10-unit system as a test example, and compared HIMOA with the famous algorithms MODE, NSGA-Ⅱ, IMOEA/D-CH, ADEA, MOHDE_SAT, MONNDE. The results show that HIMOA can provide a better Pareto solution to the 10-unit system of the DEED problem, and the convergence and distribution of the Pareto frontier obtained are better than other algorithms. The box diagram of each evaluation metric shows that HIMOA has better statistical characteristics than other algorithms.

Foundation Support

国家自然科学基金资助项目(62241301,61762001)
贵州省教育厅创新群体重大研究资助项目(黔教合KY字［2019］069)
贵州省教育厅青年科技人才成长资助项目(黔教合KY字［2020］131号)
安顺学院研究生创新专项资助项目(asxysrt(202223)号)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2023.02.0037
Publish at: Application Research of Computers Printed Article, Vol. 40, 2023 No. 9
Section: Algorithm Research & Explore
Pages: 2720-2728
Serial Number: 1001-3695(2023)09-024-2720-09

Publish History

[2023-04-20] Accepted Paper
[2023-09-05] Printed Article

Cite This Article

唐湘黔, 钱淑渠, 武慧虹. 混杂免疫多目标优化算法及对动态经济环境调度问题优化 [J]. 计算机应用研究, 2023, 40 (9): 2720-2728. (Tang Xiangqian, Qian Shuqu, Wu Huihong. Hybrid immune multi-objective optimization algorithm for dynamic emission economic dispatch [J]. Application Research of Computers, 2023, 40 (9): 2720-2728. )

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  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

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