计算物理 ›› 2025, Vol. 42 ›› Issue (1): 118-126.DOI: 10.19596/j.cnki.1001-246x.8825

• 论文 • 上一篇    下一篇

全局排序的高维多目标差分进化算法在供热管网阻力辨识中的应用

于君利1(), 周恩泽1,*(), 刘壮阔1, 徐文晓2, 杨英帅1, 相明宇1   

  1. 1. 青岛理工大学环境与市政工程学院, 山东 青岛 266000
    2. 代傲表计(济南)有限公司, 山东 济南 250000
  • 收稿日期:2023-08-28 出版日期:2025-01-25 发布日期:2025-03-08
  • 通讯作者: 周恩泽
  • 作者简介:

    于君利, 男, 硕士研究生, 研究方向为智慧供热, E-mail:

  • 基金资助:
    中国政府/世界银行/全球环境基金-中国可再生能源规模化发展二期(QUT-2017-ZX-0010)

Application of High-dimensional Multi-objective Differential Evolution Algorithm Based on Global Ordering in Resistance Identification of Heating Pipe Network

Junli YU1(), Enze ZHOU1,*(), Zhuangkuo LIU1, Wenxiao XU2, Yingshuai YANG1, Mingyu XIANG1   

  1. 1. School of Environmental and Municipal Engineering, Qingdao University of Technology, Qingdao, Shandong 266000, China
    2. Diehl Metering (Jinan) Co., Ltd., Jinan, Shangdong 250000, China
  • Received:2023-08-28 Online:2025-01-25 Published:2025-03-08
  • Contact: Enze ZHOU

摘要:

开发一种基于全局排序的高维多目标差分进化算法作为热网阻力系数辨识方法, 将多目标算法运用于热网阻力辨识中, 并改进阻力辨识的计算流程; 将模糊数学方法运用到阻力辨识过程中, 通过辨识每根管段产生一组最优解集, 依据模糊隶属度从最优解集中选取最优解, 解决了最优解的确定问题。研究结果表明: 与单目标算法相比, 基于全局排序的高维多目标差分进化算法产生的最优解集分布均匀且集中, 获得的最优解精度较高。

关键词: 供热管网, 阻力辨识, 高维多目标优化, 差分进化算法

Abstract:

A high-dimensional multi-objective differential evolution algorithm based on global ranking is developed to identify the resistance coefficient of heat supply network, and the multi-objective algorithm is applied to the resistance identification of heat supply network, and the calculation process of resistance identification is improved. The fuzzy mathematics method is applied to the process of resistance identification, a set of optimal solution is generated by identifying each pipe segment, and the optimal solution is selected from the optimal solution set according to the fuzzy membership degree. The results show that compared with the single objective algorithm, the optimal solution set generated by the high-dimensional multi-objective differential evolution algorithm based on global ranking is uniformly distributed and concentrated, and the optimal solution obtained is more accurate.

Key words: district heating network, resistance identification, high-dimensional multi-objective optimization, differential evolution algorithm