Influencing factors in energy use of housing blocks: a new methodology, based on clustering and energy simulations, for decision making in energy refurbishment projects
作者: X. CiprianoA. VellidoJ. CiprianoJ. Martí-HerreroS. Danov
作者单位: 1Centre Internacional de Mètodes Numèrics en Enginyeria (CIMNE), Building Energy and Environment Group, Edifici GAIA (TR14)
2Computer Science, Universitat Politècnica de Catalunya (UPC Barcelona Tech), Campus Nord UPC
3Centre Internacional de Mètodes Numèrics en Enginyeria (CIMNE), Building Energy and Environment Group, CIMNE-UdL Classroom
4PROMETEO Researcher, Instituto Nacional de Eficiencia Energética y Energías Renovables (INER)
刊名: Energy Efficiency, 2017, Vol.10 (2), pp.359-382
来源数据库: Springer Journal
DOI: 10.1007/s12053-016-9460-9
关键词: Building energy useEnergy building simulationClustering analysisUrban energy refurbishment
英文摘要: In recent years, big efforts have been dedicated to identify which are the factors with highest influence in the energy consumption of residential buildings. These factors include aspects such as weather dependence, user behaviour, socio-economic situation, type of the energy installations and typology of buildings. The high number of factors increases the complexity of analysis and leads to a lack of confidence in the results of the energy simulation analysis. This fact grows when we move one step up and perform global analysis of blocks of buildings. The aim of this study is to report a new methodology for the assessment of the energy performance of large groups of buildings when considering the real use of energy. We combine two clustering methods, Generative Topographic Mapping and k...
原始语种摘要: In recent years, big efforts have been dedicated to identify which are the factors with highest influence in the energy consumption of residential buildings. These factors include aspects such as weather dependence, user behaviour, socio-economic situation, type of the energy installations and typology of buildings. The high number of factors increases the complexity of analysis and leads to a lack of confidence in the results of the energy simulation analysis. This fact grows when we move one step up and perform global analysis of blocks of buildings. The aim of this study is to report a new methodology for the assessment of the energy performance of large groups of buildings when considering the real use of energy. We combine two clustering methods, Generative Topographic Mapping and k...
全文获取路径: Springer  (合作)
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影响因子:1.15 (2012)

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关键词翻译
关键词翻译
  • methodology 方法学
  • decision 决定
  • energy 能量
  • housing 外壳
  • making 制定
  • disaggregation 解聚
  • clustering 聚类
  • residential 居住的
  • reference 基准电压源
  • perform 履行