Flow Resistance Coefficient Identification of Chilled Water System based on Multi-objective Optimization and Experiment Validation

被引:0
|
作者
Hou, Zhijian [1 ]
Qu, Ming [2 ]
Wang, Zhirui [3 ]
机构
[1] Shenzhen Polytech, Sch Mech & Elect Engn, Shenzhen 518055, Peoples R China
[2] Purdue Univ, Sch Civil Engn, W Lafayette, IN 47906 USA
[3] Inner Mongolia Univ Technol, Civil Engn Inst, Hohhot 010051, Peoples R China
关键词
Flow Resistance Coefficient; Parameter Identification; Chilled water system; COOLING COILS; MODEL;
D O I
10.4028/www.scientific.net/AMM.651-653.742
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Hydraulic resistance coefficient (HRC) is a fundamental parameter that characterizes the hydraulic state of a water pipeline and significantly determines the efficiency of the water-transport process. To estimate HRC and diagnose hydraulic process fault in building air conditioning system, a novel method called multi-objective optimization (MBO) strategy was developed in the research effort. MBO is concerned with mathematical optimization problems involving more than one objective function to be optimized simultaneously. In this paper, first, the basic principle of the approach is presented. Then several experiments are conducted to identify the HRC in a real air conditioning system. And the water flow rate of each air handling terminal unit is estimated by the flow rate of primary pipe and identified HRC. The experiment results show that the model can accurately estimate HRCs. The HRCs of each pipe and terminal unit were obtained by the flow rate and the pressure difference of primary pipe without requiring geometric specifications, which is very convenient in real engineering application.
引用
收藏
页码:742 / +
页数:2
相关论文
共 50 条
  • [41] An evolutionary multi-objective optimization system for earthworks
    Parente, M.
    Cortez, P.
    Gomes Correia, A.
    EXPERT SYSTEMS WITH APPLICATIONS, 2015, 42 (19) : 6674 - 6685
  • [42] Multi-objective optimization of biomass to biomethane system
    Yan, Nana
    Ren, Baozeng
    Wu, Bin
    Bao, Di
    Zhang, Xiangping
    Wang, Jingheng
    GREEN ENERGY & ENVIRONMENT, 2016, 1 (02) : 156 - 165
  • [43] Multi-objective optimization of biomass to biomethane system
    Nana Yan
    Baozeng Ren
    Bin Wu
    Di Bao
    Xiangping Zhang
    Jingheng Wang
    Green Energy & Environment, 2016, 1 (02) : 156 - 165
  • [44] Multi-objective optimization of a multi water-to-water heat pump system using evolutionary algorithm
    Murr, R.
    Thieriot, H.
    Zoughaib, A.
    Clodic, D.
    APPLIED ENERGY, 2011, 88 (11) : 3580 - 3591
  • [45] Multi-objective optimization of aeroengine PID control based on multi-objective genetic algorithms
    Li, Yue
    Sun, Jian-Guo
    Hangkong Dongli Xuebao/Journal of Aerospace Power, 2008, 23 (01): : 174 - 178
  • [46] A Multi-Objective Evolutionary Algorithm Based on Bilayered Decomposition for Constrained Multi-Objective Optimization
    Yasuda, Yusuke
    Kumagai, Wataru
    Tamura, Kenichi
    Yasuda, Keiichiro
    IEEJ TRANSACTIONS ON ELECTRICAL AND ELECTRONIC ENGINEERING, 2025, 20 (02) : 244 - 262
  • [47] A Decomposition based Memetic Multi-objective Algorithm for Continuous Multi-objective Optimization Problem
    Wang, Na
    Wang, Hongfeng
    Fu, Yaping
    Wang, Lingwei
    2015 27TH CHINESE CONTROL AND DECISION CONFERENCE (CCDC), 2015, : 896 - 900
  • [48] A PSO-Based Hybrid Multi-Objective Algorithm for Multi-Objective Optimization Problems
    Wang, Xianpeng
    Tang, Lixin
    ADVANCES IN SWARM INTELLIGENCE, PT II, 2011, 6729 : 26 - 33
  • [49] A Species-Based Multi-Objective Genetic Algorithm for Multi-Objective Optimization Problems
    Sun Fuquan
    Wang Hongfeng
    Lu Fuqiang
    2014 11TH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION (WCICA), 2014, : 5063 - 5066
  • [50] Multi-objective optimization in variably saturated fluid flow
    Zadeh, Kouroush Sadegh
    JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS, 2009, 223 (02) : 801 - 819