Estimating the effect of retrofitting with Deconstruct+

DOI

This study employs a machine learning model to estimate the heat transfer coefficient (HTC) of a sample of dwellings in two periods, before and after retrofitting measures took place as part of the Greens Home Grant (GHG). The aim is to determine whether these measures had a statistically significant effect on reducing the HTC of the dwellings, that is, increasing their thermal efficiency. University College London (UCL) has subcontracted EDF R&D UK to undertake this study using their solution, Deconstruct+, which can estimate HTC values remotely based on a dwelling’s energy consumption and weather data.

Identifier
DOI https://doi.org/10.5522/04/29314244.v1
Related Identifier HasPart https://ndownloader.figshare.com/files/56735303
Metadata Access https://api.figshare.com/v2/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=oai:figshare.com:article/29314244
Provenance
Creator Medina Vazquez, Gustavo; Thevapalan, Anushiya; Patel, Nium
Publisher University College London UCL
Contributor Figshare
Publication Year 2025
Rights https://creativecommons.org/licenses/by/4.0/
OpenAccess true
Contact researchdatarepository(at)ucl.ac.uk
Representation
Language English
Resource Type Report; Other
Discipline Other