HVAC system optimization for energy management by evolutionary programming

被引:233
|
作者
Fong, KF
Hanby, VI
Chow, TT
机构
[1] City Univ Hong Kong, Div Bldg Sci & Technol, Kowloon, Hong Kong, Peoples R China
[2] De Montfort Univ, Inst Energy & Sustainable Dev, Leicester LE1 9BH, Leics, England
关键词
evolutionary programming; evolutionary algorithm; optimization; energy management; HVAC system;
D O I
10.1016/j.enbuild.2005.05.008
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Energy management of heating, ventilating and air-conditioning (HVAC systems is a primary concern in building projects, since the energy consumption in electricity has the highest percentage in HVAC among all building services installations and electric appliances. Without sacrifice of thermal comfort, to reset the suitable operating parameters, such as the chilled water temperature and supply air temperature, would have energy saving with immediate effect. For the typical commercial building projects, it is not difficult to acquire the reference settings for efficient operation. However, for some special projects, due to the specific design and control of the HVAC system, conventional settings may not be necessarily energy-efficient in daily operation. In this paper, the simulation-optimization approach was proposed for the effective energy management of HVAC system. Due to the complicated interrelationship of the entire HVAC system, which commonly includes the water side and air side systems, it is necessary to suggest optimum settings for different operations in response to the dynamic cooling loads and changing weather conditions throughout a year. A metaheuristic simulation-EP (evolutionary programming) coupling approach was developed using evolutionary programming, which can effectively handle the discrete, non-linear and highly constrained optimization problems, such as those related to HVAC systems. The effectiveness of this simulation-EP coupling suite was demonstrated through the establishment of a monthly optimum reset scheme for both the chilled water and supply air temperatures of the HVAC installations of a local project. This reset scheme would have a saving potential of about 7% as compared to the existing operational settings, without any extra cost. (C) 2005 Elsevier B.V. All rights reserved.
引用
收藏
页码:220 / 231
页数:12
相关论文
共 50 条
  • [1] System optimization for HVAC energy management using the robust evolutionary algorithm
    Fong, K. F.
    Hanby, V. I.
    Chow, T. T.
    [J]. APPLIED THERMAL ENGINEERING, 2009, 29 (11-12) : 2327 - 2334
  • [2] An Evolutionary Multiobjective Optimization Approach for HEV Energy Management System
    Pajares Ferrando, Alberto
    Blasco Ferragud, Xavier
    Reynoso-Meza, Gilberto
    Herrero Dura, Juan Manuel
    [J]. CONTROLO'2014 - PROCEEDINGS OF THE 11TH PORTUGUESE CONFERENCE ON AUTOMATIC CONTROL, 2015, 321 : 345 - 354
  • [3] Multi-objective optimization of HVAC system with an evolutionary computation algorithm
    Kusiak, Andrew
    Tang, Fan
    Xu, Guanglin
    [J]. ENERGY, 2011, 36 (05) : 2440 - 2449
  • [4] A Decentralized Ordinal Optimization for Energy Saving of an HVAC System
    Zhuang, Luping
    Chen, Xi
    Guan, Xiaohong
    [J]. 2016 AMERICAN CONTROL CONFERENCE (ACC), 2016, : 611 - 616
  • [5] Home HVAC Energy Management and Optimization with Model Predictive Control
    Godina, Radu
    Rodrigues, Eduardo M. G.
    Pouresmaeil, Edris
    Catalao, Joao P. S.
    [J]. 2017 1ST IEEE INTERNATIONAL CONFERENCE ON ENVIRONMENT AND ELECTRICAL ENGINEERING AND 2017 17TH IEEE INDUSTRIAL AND COMMERCIAL POWER SYSTEMS EUROPE (EEEIC / I&CPS EUROPE), 2017,
  • [6] Sustainable Data Center Energy Management through Server Workload Allocation Optimization and HVAC System
    Hsu, Ying-Feng
    Mizumoto, Chizuko
    Matsuda, Kazuhiro
    Matsuoka, Morito
    [J]. 2024 IEEE CLOUD SUMMIT, CLOUD SUMMIT 2024, 2024, : 17 - 23
  • [7] Building Energy Management Strategy Using an HVAC System and Energy Storage System
    Kim, Nam-Kyu
    Shim, Myung-Hyun
    Won, Dongjun
    [J]. ENERGIES, 2018, 11 (10)
  • [8] HVAC SYSTEM ENERGY MINIMIZATION VIA OPTIMIZATION OF LUMPED SYSTEM MODELS
    Wemhoff, Aaron P.
    [J]. PROCEEDINGS OF THE ASME INTERNATIONAL MECHANICAL ENGINEERING CONGRESS AND EXPOSITION - 2010, VOL 5, PTS A AND B, 2012, : 1339 - 1345
  • [9] Optimization of the HVAC system design to minimize primary energy demand
    Seo, Janghoo
    Ooka, Ryozo
    Kim, Jeong Tai
    Nam, Yujin
    [J]. ENERGY AND BUILDINGS, 2014, 76 : 102 - 108
  • [10] Evolutionary algorithms for multi-objective optimization in HVAC system control strategy
    Nassif, N
    Kajl, S
    Sabourin, R
    [J]. NAFIPS 2004: ANNUAL MEETING OF THE NORTH AMERICAN FUZZY INFORMATION PROCESSING SOCIETY, VOLS 1AND 2: FUZZY SETS IN THE HEART OF THE CANADIAN ROCKIES, 2004, : 51 - 56