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Energy analytics for supporting built environment decarbonisation

Energy analytics for supporting built environment decarbonisation
Energy analytics for supporting built environment decarbonisation

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 behavioral 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 wider applicability of the described numerical techniques.

Behavioural modelling, Building performance simulation, Energy efficiency, Parametric modelling, Techno-economic optimization
1876-6102
1486-1493
Tronchin, Lamberto
8527a327-51fb-4865-b99d-eab721dadec9
Manfren, Massimiliano
f2b8c02d-cb78-411d-aed1-c4d056365392
Nastasi, Benedetto
0d19eabe-134e-4cbe-9912-ff4c095410cd
Tronchin, Lamberto
8527a327-51fb-4865-b99d-eab721dadec9
Manfren, Massimiliano
f2b8c02d-cb78-411d-aed1-c4d056365392
Nastasi, Benedetto
0d19eabe-134e-4cbe-9912-ff4c095410cd

Tronchin, Lamberto, Manfren, Massimiliano and Nastasi, Benedetto (2019) Energy analytics for supporting built environment decarbonisation. Energy Procedia, 157, 1486-1493. (doi:10.1016/j.egypro.2018.11.313).

Record type: Article

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 behavioral 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 wider applicability of the described numerical techniques.

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More information

e-pub ahead of print date: 25 January 2019
Published date: January 2019
Venue - Dates: 2018 Technologies and Materials for Renewable Energy, Environment and Sustainability, TMREES 2018, Greece, 2018-09-18 - 2018-09-20
Keywords: Behavioural modelling, Building performance simulation, Energy efficiency, Parametric modelling, Techno-economic optimization

Identifiers

Local EPrints ID: 429004
URI: http://eprints.soton.ac.uk/id/eprint/429004
ISSN: 1876-6102
PURE UUID: d7f595aa-fdd5-4757-b337-1fe157c23e01
ORCID for Massimiliano Manfren: ORCID iD orcid.org/0000-0003-1438-970X

Catalogue record

Date deposited: 18 Mar 2019 17:30
Last modified: 07 Oct 2020 02:15

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