Simplified model to determine the energy demand of existing buildings. Case study of social housing in Zaragoza, Spain
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2017-08Materia/s
Materia/s Unesco
3322.05 Fuentes no Convencionales de Energía
Resumen
The refurbishment of residential buildings is fundamental to fulfil the EU's CO2 emissions and energy savings objectives. Social housing estates built during the Spanish post-war period are vulnerable areas in Spanish cities that require public economic investment for their urban regeneration, and to refurbish their buildings. Public economic resources must center on the buildings that most require these actions, which are precisely those with a higher energy demand. This article proposes a simplified model to predict heating and cooling energy demands of buildings with no insulating material layer in their envelopes, which was conducted based on the case study of social housing buildings built in the Spanish city of Zaragoza between 1945 and 1975. The model obtained herein predicts the cooling and heating energy demands of buildings from only knowing a few inputs that are easily obtained, and is useful for the energy characterisation of large residential stocks without the need of dynamic simulation. © 2017 Elsevier B.V.
The refurbishment of residential buildings is fundamental to fulfil the EU's CO2 emissions and energy savings objectives. Social housing estates built during the Spanish post-war period are vulnerable areas in Spanish cities that require public economic investment for their urban regeneration, and to refurbish their buildings. Public economic resources must center on the buildings that most require these actions, which are precisely those with a higher energy demand. This article proposes a simplified model to predict heating and cooling energy demands of buildings with no insulating material layer in their envelopes, which was conducted based on the case study of social housing buildings built in the Spanish city of Zaragoza between 1945 and 1975. The model obtained herein predicts the cooling and heating energy demands of buildings from only knowing a few inputs that are easily obtained, and is useful for the energy characterisation of large residential stocks without the need of dynamic simulation. © 2017 Elsevier B.V.
