City-scale building energy assessment
City-scale building energy assessment
The UK Government and local authorities have made commitments to reduce their CO2 emissions. This will require interventions to save energy from buildings to be deployed at scale. Previous studies into energy saving from buildings have predominantly focused on the performance of single or limited numbers of buildings, and a review of current literature indicates that there are significant uncertainties when such studies are extrapolated to project the savings potential of large scale building refurbishment. This is due to over-simplified assumptions that were generally used, which underestimate the variations in building characteristics and occupant behaviour. This seriously affects the accuracy of the modelling results, whilst the detailed assessment of individual dwellings at scale can significantly increase the time and effort required in modelling process.
In this work, a new model has been developed to provide building refurbishment considerations including the application to a greater geographic scale. To achieve this, the model is incorporated into geographic information systems (GIS), utilising accurate information of building location, dimension and other geometric characteristics. It develops a new approach to obtain building characteristics using Light Detection and Ranging (LiDAR) data, negating the need of conducting physical surveys that are required for thermal simulations of building heat losses. It has also addressed multiple gaps in data availability, resulting in the provision of rich building information, such as number of floors and total floor area, which can be utilised in building-related studies in the future.
In this research, bulk Energy Performance Certificates (EPC) were used to obtain detailed information of energy efficiency of buildings, and a model was created to extend the coverage of existing EPC datasets to all non-assessed dwellings in the city of Southampton (UK). This model was validated using the available EPC data of 40% of dwellings in Southampton. The outcome is a cost-effective and accurate method that can provide estimates of the thermal properties of non-EPC-assessed domestic buildings in UK cities.
The model approaches established here were applied to domestic buildings in Southampton, estimating the potential of energy saving through city-wide building refurbishment. The results show that the city has the potential of reducing energy consumption by approximately 295 GWh/year under the central scenario, and for other scenarios discussed in the thesis, the savings range from 184 GWh/year to 369 GWh/year. The CO2 saving potential corresponding to the central scenario is 82 kt/year (7.1% of the city’s baseline emissions in 2010), whilst the range for other scenarios is from 51 kt/year (4.4%) to 103 kt/year (8.9%). This work has shown that such modelling approach can be generalised to other cities and the outcome can provide guidance to city planners in relation to energy efficiency measures and carbon reductions.
University of Southampton
Wu, Yue
55103331-d936-4aa3-bc20-05540e35e7c1
February 2017
Wu, Yue
55103331-d936-4aa3-bc20-05540e35e7c1
Bahaj, Abubakr
a64074cc-2b6e-43df-adac-a8437e7f1b37
Wu, Yue
(2017)
City-scale building energy assessment.
University of Southampton, Doctoral Thesis, 286pp.
Record type:
Thesis
(Doctoral)
Abstract
The UK Government and local authorities have made commitments to reduce their CO2 emissions. This will require interventions to save energy from buildings to be deployed at scale. Previous studies into energy saving from buildings have predominantly focused on the performance of single or limited numbers of buildings, and a review of current literature indicates that there are significant uncertainties when such studies are extrapolated to project the savings potential of large scale building refurbishment. This is due to over-simplified assumptions that were generally used, which underestimate the variations in building characteristics and occupant behaviour. This seriously affects the accuracy of the modelling results, whilst the detailed assessment of individual dwellings at scale can significantly increase the time and effort required in modelling process.
In this work, a new model has been developed to provide building refurbishment considerations including the application to a greater geographic scale. To achieve this, the model is incorporated into geographic information systems (GIS), utilising accurate information of building location, dimension and other geometric characteristics. It develops a new approach to obtain building characteristics using Light Detection and Ranging (LiDAR) data, negating the need of conducting physical surveys that are required for thermal simulations of building heat losses. It has also addressed multiple gaps in data availability, resulting in the provision of rich building information, such as number of floors and total floor area, which can be utilised in building-related studies in the future.
In this research, bulk Energy Performance Certificates (EPC) were used to obtain detailed information of energy efficiency of buildings, and a model was created to extend the coverage of existing EPC datasets to all non-assessed dwellings in the city of Southampton (UK). This model was validated using the available EPC data of 40% of dwellings in Southampton. The outcome is a cost-effective and accurate method that can provide estimates of the thermal properties of non-EPC-assessed domestic buildings in UK cities.
The model approaches established here were applied to domestic buildings in Southampton, estimating the potential of energy saving through city-wide building refurbishment. The results show that the city has the potential of reducing energy consumption by approximately 295 GWh/year under the central scenario, and for other scenarios discussed in the thesis, the savings range from 184 GWh/year to 369 GWh/year. The CO2 saving potential corresponding to the central scenario is 82 kt/year (7.1% of the city’s baseline emissions in 2010), whilst the range for other scenarios is from 51 kt/year (4.4%) to 103 kt/year (8.9%). This work has shown that such modelling approach can be generalised to other cities and the outcome can provide guidance to city planners in relation to energy efficiency measures and carbon reductions.
Text
Final e-thesis for e-prints WU 24262315
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Published date: February 2017
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Local EPrints ID: 418312
URI: http://eprints.soton.ac.uk/id/eprint/418312
PURE UUID: a24ccca1-a3c2-4543-82cb-6e5726139818
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Date deposited: 27 Feb 2018 17:34
Last modified: 16 Mar 2024 05:27
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Author:
Yue Wu
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