Repository of Deep Renovation Packages Based on Industrialized Solutions: Definition and Application

Renovation Wave aims to boost the uptake of deep renovation towards the CO2 emission targets for 2030. In this perspective, there is the need of technologies and solution sets for improving the deep renovation process as well as demonstrating the performances for supporting the stakeholders in the d...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Sustainability 2021-06, Vol.13 (11), p.6412
Hauptverfasser: Pernetti, Roberta, Pinotti, Riccardo, Lollini, Roberto
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:Renovation Wave aims to boost the uptake of deep renovation towards the CO2 emission targets for 2030. In this perspective, there is the need of technologies and solution sets for improving the deep renovation process as well as demonstrating the performances for supporting the stakeholders in the decision-making process. To cope with the issue, this work presents a methodology for setting up a repository of building deep renovation packages that integrates industrialised facade technologies and more traditional solutions. The performances feeding into the repository have been evaluated by means of transient detailed simulations on a set of reference buildings in representative European climate conditions. The renovation packages are evaluated in terms of key performance indicators dealing with five areas: energy, comfort, pollutant emissions, cost, and renovation time. The defined repository includes 289 assessed technology packages and associated performances across Europe, providing a comprehensive support to identify the most effective solutions according to the user needs. The paper presents the application of the repository with two examples of stakeholders’ decision-making paths for selecting the deep renovation packages according to different priorities and expected targets.
ISSN:2071-1050
2071-1050
DOI:10.3390/su13116412