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City-wide building energy efficiency assessment using EPC data

City-wide building energy efficiency assessment using EPC data
City-wide building energy efficiency assessment using EPC data
The Energy Performance Certificate (EPC) requirements in Europe have provided rich data of energy efficiency status of individual buildings at scale, allowing appropriate assessments to be carried out without the need of conducting additional surveys. By 2012, the EPC data in England and Wales in the UK has reached a coverage of up to 45% of the entire building stock (DECC 2014), and the number of new certificates added every year is over 1 million. The work presented here seeks to understand the potential of using such dataset to deliver systematic analysis of energy efficiency of buildings at a city scale. This study utilises all EPC datasets available for the city of Southampton, UK, and developed an automatic geographic-referencing methodology so the EPC data can be integrated onto geographic information systems (GIS). Such methodology allows large quantity of EPC data to be analysed spatially, facilitating the assessment of energy performance of different regions in a city. The results show clearly areas in the city that have the lowest or highest level of performance in terms of buildings’ energy efficiency, and revealed the impact of certain building intervention measures (such insulation, double glazing) on the energy consumption within the considered buildings. The analyses show that factors such as the existence of high streets and new building developments have significant influence on the energy efficiency in the city where these are present. The geographic-referencing methodology developed in this study has the potential to be utilised in a wide range of subjects, bridging the current gap of data availability, allowing building related datasets to be incorporated with GIS analysis.
2363-9075
1-7
Wu, Yue
a9704c03-5dad-4496-8472-87af8e14a712
Blunden, Luke
28b4a5d4-16f8-4396-825b-4f65639d2903
Bahaj, Abubakr
a64074cc-2b6e-43df-adac-a8437e7f1b37
Wu, Yue
a9704c03-5dad-4496-8472-87af8e14a712
Blunden, Luke
28b4a5d4-16f8-4396-825b-4f65639d2903
Bahaj, Abubakr
a64074cc-2b6e-43df-adac-a8437e7f1b37

Wu, Yue, Blunden, Luke and Bahaj, Abubakr (2017) City-wide building energy efficiency assessment using EPC data. Future Cities and Environment, 1 (7), 1-7. (doi:10.5334/fce.10). (In Press)

Record type: Article

Abstract

The Energy Performance Certificate (EPC) requirements in Europe have provided rich data of energy efficiency status of individual buildings at scale, allowing appropriate assessments to be carried out without the need of conducting additional surveys. By 2012, the EPC data in England and Wales in the UK has reached a coverage of up to 45% of the entire building stock (DECC 2014), and the number of new certificates added every year is over 1 million. The work presented here seeks to understand the potential of using such dataset to deliver systematic analysis of energy efficiency of buildings at a city scale. This study utilises all EPC datasets available for the city of Southampton, UK, and developed an automatic geographic-referencing methodology so the EPC data can be integrated onto geographic information systems (GIS). Such methodology allows large quantity of EPC data to be analysed spatially, facilitating the assessment of energy performance of different regions in a city. The results show clearly areas in the city that have the lowest or highest level of performance in terms of buildings’ energy efficiency, and revealed the impact of certain building intervention measures (such insulation, double glazing) on the energy consumption within the considered buildings. The analyses show that factors such as the existence of high streets and new building developments have significant influence on the energy efficiency in the city where these are present. The geographic-referencing methodology developed in this study has the potential to be utilised in a wide range of subjects, bridging the current gap of data availability, allowing building related datasets to be incorporated with GIS analysis.

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Accepted/In Press date: 13 December 2017

Identifiers

Local EPrints ID: 417585
URI: http://eprints.soton.ac.uk/id/eprint/417585
ISSN: 2363-9075
PURE UUID: 88370f26-e075-4945-bf57-829cb0abc173
ORCID for Yue Wu: ORCID iD orcid.org/0000-0002-4112-7935
ORCID for Luke Blunden: ORCID iD orcid.org/0000-0002-0046-5508
ORCID for Abubakr Bahaj: ORCID iD orcid.org/0000-0002-0043-6045

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Date deposited: 05 Feb 2018 17:30
Last modified: 18 Feb 2021 17:17

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