In line with the energy targets for the coming decades, many European countries have implemented incentive policies to promote the energy retrofit of buildings. Hence, it is necessary to consider real energy consumption data when developing large-scale policies to accurately define potential improvements in energy consumption. This paper presents a data-driven approach to determining the energy consumption of 227 social housing buildings located in four northern Italian cities. A monitoring campaign during three consecutive winter seasons (2016–17, 2017–18, and 2018–19) provided the data needed to analyse the buildings’ consumption using calculated energy performance indexes. The performance indexes were normalised using the degree-day (DD) method, making them useful references for assessing similar housing stock in different climatic contexts, as well as on an international scale. A 90% consistency within the building sample strengthened the reliability of the results. Moreover, the developed method for data analysis is replicable in a stepwise manner for other types of building stock if energy consumption data from a representative sample are available to obtain practical reference values.
Energy performance indexes based on monitored data of social housing buildings in Northern Italy
Ferrari, Simone;Blázquez, Teresa;Dall'O', Giuliano
2021-01-01
Abstract
In line with the energy targets for the coming decades, many European countries have implemented incentive policies to promote the energy retrofit of buildings. Hence, it is necessary to consider real energy consumption data when developing large-scale policies to accurately define potential improvements in energy consumption. This paper presents a data-driven approach to determining the energy consumption of 227 social housing buildings located in four northern Italian cities. A monitoring campaign during three consecutive winter seasons (2016–17, 2017–18, and 2018–19) provided the data needed to analyse the buildings’ consumption using calculated energy performance indexes. The performance indexes were normalised using the degree-day (DD) method, making them useful references for assessing similar housing stock in different climatic contexts, as well as on an international scale. A 90% consistency within the building sample strengthened the reliability of the results. Moreover, the developed method for data analysis is replicable in a stepwise manner for other types of building stock if energy consumption data from a representative sample are available to obtain practical reference values.File | Dimensione | Formato | |
---|---|---|---|
1-s2.0-S0306261921006838-main.pdf
Accesso riservato
:
Publisher’s version
Dimensione
5.51 MB
Formato
Adobe PDF
|
5.51 MB | Adobe PDF | Visualizza/Apri |
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.