He, M. Dynamic modelling of a large scale retrofit programme for the housing stock in the north east of england.pdf (445.81 kB)

Dynamic modelling of a large scale retrofit programme for the housing stock in the North East of England

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conference contribution
posted on 19.12.2014, 11:37 by Candy He, Timothy Lee, Simon Taylor, Steven Firth, Kevin Lomas
Housing stock models have long been employed to estimate the baseline energy demand of the existing housing stock, as well as to predict the effectiveness of applying different retrofit measures and renewable technologies on reducing the energy demand and corresponding CO2 emissions. This research aims to develop a dynamic housing stock model to simulate the hourby-hour energy demands of 1.2 million dwellings in the North East (NE) of England using the 2008-9 English Housing Survey (EHS) data. The model is validated by comparison to a steady-state energy model. Using the model, new results predicting the impact of a large scale retrofit programme for the NE housing stock are generated.

Funding

This work was carried out as part of the Self Conserving Urban Environments (SECURE) project which was funded by the Engineering and Physical Science Research Council (EPSRC) under their Sustainable Urban Environment programme (grant EP/I002154/1). SECURE is a consortium of four UK universities: Newcastle University, the University of Sheffield, the University of Exeter and Loughborough University. The project website is https://www.secure-preject.org/

History

School

  • Architecture, Building and Civil Engineering

Published in

USAR 2014

Pages

- - ?

Citation

HE, M. ... et al., 2014. Dynamic modelling of a large scale retrofit programme for the housing stock in the North East of England. IN: Proceedings of the 2nd International Conference on Urban Sustainability and Resilience, London, UK, 3 – 5 November 2014.

Publisher

Urban Sustainability and Resilience (USAR) Conference Series

Version

VoR (Version of Record)

Publisher statement

This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/

Publication date

2014

Notes

This is a conference paper.

ISSN

2051-1361

Language

en

Location

London, UK

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