Multi-objective optimization of wind power systems based on RSM and NSGA-Ⅱ methods

被引：0
|
作者：
Cao Y. [1 ]
Wen C. [1 ,2 ]
Liu Z. [1 ,3 ]
Zhang S. [4 ]
Fang Y. [5 ]
Wang J. [1 ,2 ]
机构：
[1] College of Energy and Power Engineering Inner Mongolia University of Technology, Hohhot
[2] Key Laboratory of Wind Energy and Solar Energy Utilization Technology of Ministry of Education, Hohhot
[3] College of Mechanical Engineering, Inner Mongolia University of Technology, Hohhot
[4] New Energy Company of Mengneng Group, Hohhot
[5] Baotou Light Industry Vocational Technical College, Baotou
来源：
Taiyangneng Xuebao/Acta Energiae Solaris Sinica | 2022年 / 43卷 / 01期
关键词：
Energy storage; Exergoeconomic analysis; Multiobjective optimization; Power fluctuation; Wind turbines;
D O I：
10.19912/j.0254-0096.tynxb.2021-0467
中图分类号：
学科分类号：
摘要：
Aiming at the problems of low efficiency and poor economy caused by the complex and variable operating conditions of wind power storage systems, a multi-objective optimization method based on the combination of response surface method (RSM) and non-dominant genetic algorithm (NSGA-Ⅱ) is proposed. Firstly, the system exergy balance and exergy cost conservation model is established, and the exergy efficiency and cost difference are used as system evaluation indicators; secondly, the design conditions are combined with variable speed, battery type, battery charge and discharge state, and power fluctuation amount, and the central composite design is adopted The experiment (CCD) obtained 16 sets of sample data of operating conditions, and obtained the regression equations of exergy efficiency and cost difference according to the RSM method; then the reliability of the model was verified by analysis of variance; finally, the optimization was optimized with the maximum exergy efficiency and the minimal cost difference. With dual goals, the model is solved with the combined method of RSM and NSGA-Ⅱ, and the best operating conditions are selected according to the results, thereby improving the exergy efficiency and exergy economy of the system. © 2022, Solar Energy Periodical Office Co., Ltd. All right reserved.
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页码：161 / 168
页数：7
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