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基于现场调研和分项计量数据的冷水机组序列控制策略分析
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  • 英文篇名:Analysis of Control Strategy for Chillers Based on Field Investigation and Partial Measurement Data
  • 作者:张炜杰 ; 李佳璐 ; 张钊宁 ; 李铮伟
  • 英文作者:ZHANG Wei-jie;LI Jia-lu;ZHANG Zhao-ning;LI Zheng-wei;School of Mechanical and Power Engineering,Tongji University;
  • 关键词:冷水机组 ; 运行策略 ; 调研 ; 分项计量
  • 英文关键词:chillers;;operational strategy;;field study;;sub-metering data
  • 中文刊名:FCYY
  • 英文刊名:Building Energy Efficiency
  • 机构:同济大学机械与能源工程学院;
  • 出版日期:2019-04-25
  • 出版单位:建筑节能
  • 年:2019
  • 期:v.47;No.338
  • 基金:中国国家青年科学基金(51508394)
  • 语种:中文;
  • 页:FCYY201904005
  • 页数:6
  • CN:04
  • ISSN:21-1540/TU
  • 分类号:32-37
摘要
冷水机组的运行能耗约占整个空调系统能耗的30%~40%,冷水机组运行控制策略的优劣对建筑节能管理有很重要的作用。然而实际管理方对机组的运行管理不够重视,操作人员的专业知识不够,并且存在粗放操作的行为,因此冷水机组运行策略优化控制具有很大的节能潜力。为了更好地了解目前冷水机组的运行现状并指导冷水机组的运行,对上海市建筑进行实地调研,并结合分项计量数据,分析目前冷水机组的运行策略,总结出运行人员的运行策略。得到的结论显示目前采用的冷水机组控制策略过于简单,不注重冷水机组的优化控制,实施优化控制策略具有很大的节能潜力。
        The energy consumption of chillers accounts for about 30% to 40% of the energy consumption of the entire air-conditioning system,advantages and disadvantages of chiller operation control strategies play an important role in building energy management. However, the insufficient attention paid to the operation and management of the system and relatively low operator's expertise lead to great potential for energy conservation. In order to better understand the current status of chiller operations and guide the operation of chillers,the authors conducted field research in public buildings in Shanghai,analyzed the current chiller operation strategy based on sub-metering data,and identified the operation strategy of the operating personnel. The conclusions obtained in this paper show that the currently adopted chiller control strategy is simple and non-optimal,implementation of an optimized control strategy has great potential for energy conservation.
引文
[1]江亿.我国建筑能耗状况与节能重点[J].建设科技,2007,(5):26-29.
    [2]Library W E.American society of heating,refrigerating and air-conditioning engineers[J].International Journal of Refrigeration,2012,2(3):56-57.
    [3]Yung-Chung Chang,LIN Jui-kun,Meng-Hsuan Chuang.Optimal chiller loading by genetic algorithm for reducing energy consumption[J].Energy and Buildings,2005,37(2):147-155.
    [4]CHANG Y.An innovative approach for demand side management-optimal chiller loading by simulated annealing[J].Energy,2006,31(12):1883-1896.

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