The first part of this study provided a discussion about the methodological approach for designing energy refurbishment measures of buildings. The case study is a building owned by University of Molise, in Campobasso, a cold Italian city. The reference scenario is a numerical model built after deep investigations, and thus surveys, questionnaires, documents and experimental measurements on the real building. Then, a calibrated energy model was presented. In this second part, starting from the calibrated model, some energy retrofit measures have been implemented. The obtained results allow to discuss two key points for researches in matter of energy refurbishment of buildings: a) the importance of using validated models to simulate the present performance; b) the environmental benefits and the economic implications of a deep energy refurbishment.

Energy refurbishment of a University building in cold Italian backcountry. Part 2: Sensitivity studies and optimization

Vanoli, Giuseppe Peter
2019-01-01

Abstract

The first part of this study provided a discussion about the methodological approach for designing energy refurbishment measures of buildings. The case study is a building owned by University of Molise, in Campobasso, a cold Italian city. The reference scenario is a numerical model built after deep investigations, and thus surveys, questionnaires, documents and experimental measurements on the real building. Then, a calibrated energy model was presented. In this second part, starting from the calibrated model, some energy retrofit measures have been implemented. The obtained results allow to discuss two key points for researches in matter of energy refurbishment of buildings: a) the importance of using validated models to simulate the present performance; b) the environmental benefits and the economic implications of a deep energy refurbishment.
http://www.sciencedirect.com/science/journal/18766102
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11695/85780
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