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Assessment of operating performance of chiller systems using cluster analysis

机译:使用聚类分析评估冷却器系统的运行性能

摘要

This study assesses the operating performance of chiller systems by using cluster analysis. Cluster analysis is a statistical tool used to identify groups of individuals similar to each other but different from individuals in other groups. This serves the purpose of classifying what operating condition constitutes a high or low system coefficient of performance (COP). A system with five chillers of two different cooling capacities has been studied. Seven typical operating variables for each chiller were monitored at half-hour intervals over a year. After dividing around 17,000 sets of operating data into five cluster groups by the two-step cluster analysis, it is possible to identify the sensitivity of system COP to each operating variable and, in turn, to prioritize the critical variables influencing the system COP. The significance of this study is to demonstrate a systematic method to rank operating variables according to their influence on the COP of any given chiller system and hence to improve settings of the controllable variables to increase the COP.
机译:本研究通过使用聚类分析评估冷却器系统的运行性能。聚类分析是一种统计工具,用于识别彼此相似但与其他组别不同的个人组。这用于对构成高或低系统性能系数(COP)的运行条件进行分类的目的。已经研究了具有五个具有两种不同制冷量的制冷机的系统。在一年中,每隔半小时监控一次每个冷却器的七个典型运行变量。通过两步聚类分析将大约17,000套运行数据划分为五个聚类组后,可以确定系统COP对每个运行变量的敏感度,进而可以对影响系统COP的关键变量进行优先级排序。这项研究的意义在于证明一种系统的方法,可以根据操作变量对任何给定冷却器系统的COP的影响对操作变量进行排名,从而改善可控制变量的设置以提高COP。

著录项

  • 作者

    Yu FW; Chan KT;

  • 作者单位
  • 年度 2012
  • 总页数
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类

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