The identification of techno-economically feasible decarbonisation paths and sustainability transitions for the built environment is a necessary task for research today and building stock renovation processes can act in synergy with innovative economic and technological development paradigms to achieve different types of benefits such as economic growth and employment, together with resource efficiency and sustainability for the whole sector. The research presented aims at selecting the most relevant data analysis processes and techniques to respond to practical technical questions and to support decision-making in the built environment, at multiple scales of analysis, from individual buildings, to building stock and urban environment. The research aims to indicate in this way the possibility to join the micro-scale view, involving technological and behavioural issues in buildings, and the macro-scale view, involving strategic problems at market and policy levels for energy and sustainability planning. Further, the combined use of modelling techniques with large scale data acquisition and processing could guarantee multiple feed-backs from measured data, useful for the evolution, first of all, of design and operation practices in building but also, more in general, of the whole value chain of the sector. A synthesis and integration of modelling methodologies is presented through case studies, showing a path to improve transparency of performance assessment across building life cycle phases. Finally, multivariate data visualization techniques are presented to ease the use of the numerical techniques described, ensuring a wider applicability.

DECARBONISATION OF BUILDING STOCK: DATA ANALYSIS TECHNIQUES TO EXTRACT USEFUL INSIGHTS FOR THE SUPPORT OF RENOVATION PROCESSES

L. Tronchin
;
2018

Abstract

The identification of techno-economically feasible decarbonisation paths and sustainability transitions for the built environment is a necessary task for research today and building stock renovation processes can act in synergy with innovative economic and technological development paradigms to achieve different types of benefits such as economic growth and employment, together with resource efficiency and sustainability for the whole sector. The research presented aims at selecting the most relevant data analysis processes and techniques to respond to practical technical questions and to support decision-making in the built environment, at multiple scales of analysis, from individual buildings, to building stock and urban environment. The research aims to indicate in this way the possibility to join the micro-scale view, involving technological and behavioural issues in buildings, and the macro-scale view, involving strategic problems at market and policy levels for energy and sustainability planning. Further, the combined use of modelling techniques with large scale data acquisition and processing could guarantee multiple feed-backs from measured data, useful for the evolution, first of all, of design and operation practices in building but also, more in general, of the whole value chain of the sector. A synthesis and integration of modelling methodologies is presented through case studies, showing a path to improve transparency of performance assessment across building life cycle phases. Finally, multivariate data visualization techniques are presented to ease the use of the numerical techniques described, ensuring a wider applicability.
2018
Proceedings of the SEEP 2018 - 11th INTERNATIONAL CONFERENCE ON SUSTAINABLE ENERGY & ENVIRONMENTAL PROTECTION
1
6
L. Tronchin; M. Manfren; B. Nastasi
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/636297
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