The vast data collected since the enforcement of building energy labelling in Italy has provided valuable information that is useful for planning the future of building energy efficiency. However, the indicators provided through energy certificates are not suitable to support decisions, which target building energy retrofit in a regional scale. Considering the bias of the energy performance index toward a building's shape, decisions based on this index will favor buildings with a specific geometric characteristics. This study tends to overcome this issue by introducing a new indicator, tailored to rank buildings based on retrofitable characteristics. The proposed framework is validated by a case study, in which a large dataset of office buildings are assigned with the new index. Results indicate that the proposed indicator succeeds to extract a single index, which is representative of all building characteristics subject to energy retrofit. A new labeling procedure is also compared with the conventional classification of buildings. It is observed that the proposed labels properly partitions the dataset, according to buildingsâ potential to undergo energy retrofit.
Building energy retrofit index for policy making and decision support at regional and national scales
Khayatian, Fazel;Sarto, Luca;Dall'o, Giuliano
2017-01-01
Abstract
The vast data collected since the enforcement of building energy labelling in Italy has provided valuable information that is useful for planning the future of building energy efficiency. However, the indicators provided through energy certificates are not suitable to support decisions, which target building energy retrofit in a regional scale. Considering the bias of the energy performance index toward a building's shape, decisions based on this index will favor buildings with a specific geometric characteristics. This study tends to overcome this issue by introducing a new indicator, tailored to rank buildings based on retrofitable characteristics. The proposed framework is validated by a case study, in which a large dataset of office buildings are assigned with the new index. Results indicate that the proposed indicator succeeds to extract a single index, which is representative of all building characteristics subject to energy retrofit. A new labeling procedure is also compared with the conventional classification of buildings. It is observed that the proposed labels properly partitions the dataset, according to buildingsâ potential to undergo energy retrofit.File | Dimensione | Formato | |
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