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Using principal component and cluster analysis in the heating evaluation of the school building sector

机译:在学校建筑部门的供热评估中使用主成分和聚类分析

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摘要

In the field of energy savings in buildings, the interest towards the school sector is deeply motivated: schools have standard energy demands and high levels of environmental comforts should be guaranteed. The University of Athens in collaboration with the School Authority of Greece undertook a complete program on energy classification and environmental quality of school buildings. Data on energy consumptions were gathered and analysed with the participation of 1100 schools from all the prefectures of Greece. The data have been provided by the school authority of the country (OSK), in collaboration with the management of each school building. With regards to the size of the building and the external climate variability (HDD-method) energy normalization techniques have been applied in order to homogenize the data set. An energy classification tool has been created through clustering techniques, using the collected data regarding the heating energy consumption and as a result five energy classes have been defined. To evaluate the potential energy conservation for each class, the typical characteristics of school buildings belonging to an energy class have to be identified. A new methodology based on the use of the principal components analysis (PCA) has been developed. The method allows to define in an accurate way the typical building of each energy class and thus to perform analysis on the potential energy savings for the specific group of school buildings. By reducing the dimensionality of the problem, a bi-dimensional graphic in the first two PCs coordinate system promotes the understanding of the correlation between the examined variables, as well as the determination of sub-groups of school buildings with similar characteristics. The typical school of seven variables sample is defined as the closest to the medians in the principal components' coordinate system.
机译:在建筑物的节能领域中,对学校部门的兴趣被深深地激发:学校有标准的能源需求,应保证高水平的环境舒适度。雅典大学与希腊学校管理局合作,对学校建筑的能源分类和环境质量进行了完整的计划。来自希腊所有州的1100所学校参与了能源消耗数据的收集和分析。数据是由该国的学校当局(OSK)与每所学校建筑物的管理人员合作提供的。关于建筑物的大小和外部气候可变性(HDD方法),已应用能源标准化技术以使数据集均匀化。通过使用收集到的有关加热能耗的数据,通过聚类技术创建了一种能源分类工具,因此定义了五个能源类别。为了评估每个班级的节能潜力,必须确定属于能源班级的教学楼的典型特征。已经开发了一种基于使用主成分分析(PCA)的新方法。该方法允许以准确的方式定义每个能源类别的典型建筑物,从而对特定建筑物群的潜在节能进行分析。通过减小问题的维数,前两个PC坐标系中的二维图形可以促进对检查变量之间相关性的了解,以及确定具有相似特征的教学楼的子类。典型的由七个变量组成的样本定义为最接近主成分坐标系中的中位数。

著录项

  • 来源
    《Applied Energy》 |2010年第6期|2079-2086|共8页
  • 作者单位

    University of Ioannina, Department of Environmental and Natural Resources Management, 2 G. Seferis Str., 30100 Agrinio, Greece;

    University of La Rochelle, Civil and Mechanical Engineering Department, France;

    University of Athens, Department of Physics, Division of Applied Physics, Laboratory of Meteorology, University Campus, Building PHYS-V, Athens GR 15784, Greece;

    University of Ioannina, Department of Environmental and Natural Resources Management, 2 G. Seferis Str., 30100 Agrinio, Greece;

    University of Peloponnesus, Faculty of Human Sciences and Cultural Studies, Department of History, Archaeology and Cultural Heritage Management, Kalamata, Greece;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    energy rating; cluster analysis; principal components analysis; school buildings;

    机译:能量等级聚类分析;主成分分析;学校建筑;
  • 入库时间 2022-08-18 00:10:23

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