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UK Housing Stock Models Using SAP: The Case for Heating Regime Change

Received: 15 August 2016    Accepted: 27 August 2016    Published: 13 September 2016
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Abstract

Cutting energy use in housing will play a key role in the UK’s efforts to reduce climate change emissions in line with international commitments. Much UK Government policy is based on modelling present and future emissions using assumptions from SAP, the Standard Assessment Procedure. This paper compares SAP-based modelling against measured gas consumption in 405 dwellings that were monitored in the Energy Follow-Up Survey, an extension of the English Housing Survey. The combined EFUS/EHS provides comprehensive information about space heating energy use for a sample of dwellings: detailed physical data, user behaviour, and measured energy use. Very poor model versus measurement agreement is observed at the individual dwelling level – the average difference is 45%. Much better agreement is observed when applying typical EFUS regimes of 20°C mean demand temperature, 10 hours of heating a day for weekdays and weekends, and a heating season of six months, and comparing average results. Comparisons for the 405 dwellings and an EFUS subset of 1,191 dwellings are both in agreement to within 2%, whilst average 2010 and 2011 sub-national estimates are in agreement to 3% of DUKES figures. The authors recommend changing SAP heating regimes to a mean demand temperature of 20°C, 10 hours of heating a day for weekdays and weekends, and a heating season of six months.

Published in Science Journal of Energy Engineering (Volume 4, Issue 2)
DOI 10.11648/j.sjee.20160402.11
Page(s) 12-22
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Household Energy, Energy Model, Cambridge Housing Model, SAP, Green Deal, Energy Follow-up Survey

References
[1] H. M. Government. 2008. Climate Change Act 2008. The Stationery Office Ltd, Norwich, UK.
[2] Department of Energy & Climate Change. 2013a. Energy Consumption in the UK (ECUK) Chapter 3: Domestic energy consumption in the UK between 1970 and 2012. London: DECC.
[3] Palmer, J. M. and Cooper, I. 2014. Great Britain’s Housing Energy Fact File 2013. London: DECC.
[4] Department of Energy & Climate Change. 2015. Energy Consumption in the UK (ECUK) Domestic data tables 2015 Update. London: DECC.
[5] Department of Energy & Climate Change (DECC). 2010. SAP 2009: The Government’s Standard Assessment Procedure for Energy Rating of Dwellings. 2009 edition, revised October 2010. Watford: Building Research Establishment.
[6] Anderson, B. R., Chapman, P. F., Cutland, N. G., Dickson, C. M., Doran, S. M., Henderson, G., Henderson, J. H., Iles, P. J., Kosima, L., Shorrock, L. D. 2002. BREDEM-8 Model Description (2001 Update). Building Research Establishment (BRE), Garston, UK.
[7] Jones, P., Patterson, J., Lannon, S. 2007. Modelling the built environment at an urban scale – energy and health impacts in relation to housing. Landscape and Urban Planning, 83 (1), 39-49.
[8] Atkinson, J. G. B., Jackson, T. and Mullings-Smith, E. 2009. Market influence on the low carbon energy refurbishment of existing multi-residential buildings. Energy Policy, 37 (7), 2582-2593.
[9] Cheng, V. and Steemers, K. 2011. Modelling domestic energy consumption at district scale: A tool to support national and local energy policies. Environmental Modelling & Software, 26 (10), 1186-1198.
[10] Hughes M., Palmer J., Cheng V., Shipworth D. 2013. Sensitivity and uncertainty analysis of England's housing energy model, Building Research and Information, 41 (2), 156-167.
[11] Department of Energy & Climate Change. 2012a. How the Green Deal will reflect the in-situ performance of energy efficiency measures. London: DECC.
[12] Department for Communities and Local Government (CLG). 2015. English Housing Survey HOMES 2013. July 2015, London. DCLG.
[13] Shipworth, M., Firth, S. K., Gentry, M., Wright, A. J., Shipworth, D., Lomas. K. J. 2010. Central Heating thermostat settings and timing: building demographics. Building Research & Information, 38 (1), 50-69.
[14] Kane, T., Firth, S. K., Allinson, D., Irvine, K. N., Lomas, K. J. 2011. Understanding occupant heating practices in UK dwellings. World Renewables Energy Congress 2011; Energy End-Use Efficiency Issues, Linköping, Sweden, 8-11 May 2011.
[15] Kavgic, M., Mumovic, D., Summerfield, A., Stevanovic, Z., Ecium-Djuric, O. 2013. Uncertainty and modeling energy consumption: Sensitivity analysis for a city-scale domestic energy model. Energy and Buildings, 60, 1-11.
[16] Hughes M., Palmer J., Cheng V., Shipworth D. 2014. Global sensitivity analysis of England's housing energy model, Journal of Building Performance Simulation, Online 26 June 2014.
[17] Department of Energy and Climate Change (DECC). 2012b. Digest of UK Energy Statistics (DUKES) 2012: Long-term trends. London: DECC.
[18] H. M. Government. 2010. Approved Document Part L1A: Conservation of fuel and power in new dwellings (2010 Edition). London: Communities and Local Government.
[19] Department for Communities and Local Government (CLG). 2012. English Housing Survey HOMES 2010. July 2013, London. DCLG.
[20] Building Research Establishment (BRE). 2013a. Energy Follow Up Survey 2011: Report 11 – Methodology BRE report number 288851, Dec 2013. London: DECC.
[21] Building Research Establishment (BRE). 2013b. Energy Follow Up Survey 2011: Report 1 - Summary of findings, BRE report number 289605, Dec 2013. London: DECC.
[22] Building Research Establishment (BRE). 2013c. Energy Follow Up Survey 2011: Report 4 – Main heating systems, BRE report number 286733a, Dec 2013. London: DECC.
[23] Shorrock, L. D. and Dunster, J. E. 1997. The physically-based model BREHOMES and its use in deriving scenarios for the energy use and CO2 emissions of the UK housing stock, Energy Policy, 25 (10), 27-37.
[24] Johnston, D. Lowe, R., Bell M. 2005. An Exploration of the Technical Feasibility of Achieving CO2 Emission Reductions in Excess of 60% Within the Housing Stock by the Year 2050, Energy Policy, 33 (13), 1643-1659.
[25] Shorrock, L. D., Dunster, J. E., Seale, C. F., Eppel, H., Lomas, K. J. 1994. Testing BREDEM-8 Against Measured Consumption Data and Against Simulation Models, Proceedings of Building Environmental Performance, BEPAC 1994.
[26] Taylor, S., Allinson, D., Firth, S., Lomas, K. 2013. Dynamic energy modelling of UK housing: evaluation of alternative approaches, Proceedings of BS 2013: 13th Conference of International Building Performance Simulation Association, Chambéry, France.
[27] Department of Energy & Climate Change. 2014. National Energy Efficiency Data-Framework: Summary of analysis using the National Energy Efficiency Data-Framework (NEED). London: DECC.
[28] Hughes M., Palmer J., Pope P. 2013. A Guide to the Cambridge Housing Model. London: DECC.
[29] Huebner, G. M., McMichael, M., Shipworth, D., Shipworth, M., Durand-Daubin, M., Summerfield, A. 2013. Heating patterns in English homes: Comparing results from a national survey against common model assumptions. Building and Environment, 70, 298–305.
[30] Firth, S. K., Lomas, K. J., Wright, A. J. 2010. Targeting household energy-efficiency measures using sensitivity analysis. Building Research and Information, 38 (1), 25-41.
[31] Hopfe, C. J. and Hensen, J. L. M. 2011. Uncertainty analysis in building performance simulation for design support. Energy and Buildings, 43 (10), 2798-2805.
Cite This Article
  • APA Style

    Martin Hughes, Peter Pope, Jason Palmer, Peter Armitage. (2016). UK Housing Stock Models Using SAP: The Case for Heating Regime Change. Science Journal of Energy Engineering, 4(2), 12-22. https://doi.org/10.11648/j.sjee.20160402.11

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    ACS Style

    Martin Hughes; Peter Pope; Jason Palmer; Peter Armitage. UK Housing Stock Models Using SAP: The Case for Heating Regime Change. Sci. J. Energy Eng. 2016, 4(2), 12-22. doi: 10.11648/j.sjee.20160402.11

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    AMA Style

    Martin Hughes, Peter Pope, Jason Palmer, Peter Armitage. UK Housing Stock Models Using SAP: The Case for Heating Regime Change. Sci J Energy Eng. 2016;4(2):12-22. doi: 10.11648/j.sjee.20160402.11

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  • @article{10.11648/j.sjee.20160402.11,
      author = {Martin Hughes and Peter Pope and Jason Palmer and Peter Armitage},
      title = {UK Housing Stock Models Using SAP: The Case for Heating Regime Change},
      journal = {Science Journal of Energy Engineering},
      volume = {4},
      number = {2},
      pages = {12-22},
      doi = {10.11648/j.sjee.20160402.11},
      url = {https://doi.org/10.11648/j.sjee.20160402.11},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.sjee.20160402.11},
      abstract = {Cutting energy use in housing will play a key role in the UK’s efforts to reduce climate change emissions in line with international commitments. Much UK Government policy is based on modelling present and future emissions using assumptions from SAP, the Standard Assessment Procedure. This paper compares SAP-based modelling against measured gas consumption in 405 dwellings that were monitored in the Energy Follow-Up Survey, an extension of the English Housing Survey. The combined EFUS/EHS provides comprehensive information about space heating energy use for a sample of dwellings: detailed physical data, user behaviour, and measured energy use. Very poor model versus measurement agreement is observed at the individual dwelling level – the average difference is 45%. Much better agreement is observed when applying typical EFUS regimes of 20°C mean demand temperature, 10 hours of heating a day for weekdays and weekends, and a heating season of six months, and comparing average results. Comparisons for the 405 dwellings and an EFUS subset of 1,191 dwellings are both in agreement to within 2%, whilst average 2010 and 2011 sub-national estimates are in agreement to 3% of DUKES figures. The authors recommend changing SAP heating regimes to a mean demand temperature of 20°C, 10 hours of heating a day for weekdays and weekends, and a heating season of six months.},
     year = {2016}
    }
    

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  • TY  - JOUR
    T1  - UK Housing Stock Models Using SAP: The Case for Heating Regime Change
    AU  - Martin Hughes
    AU  - Peter Pope
    AU  - Jason Palmer
    AU  - Peter Armitage
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    PY  - 2016
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    DO  - 10.11648/j.sjee.20160402.11
    T2  - Science Journal of Energy Engineering
    JF  - Science Journal of Energy Engineering
    JO  - Science Journal of Energy Engineering
    SP  - 12
    EP  - 22
    PB  - Science Publishing Group
    SN  - 2376-8126
    UR  - https://doi.org/10.11648/j.sjee.20160402.11
    AB  - Cutting energy use in housing will play a key role in the UK’s efforts to reduce climate change emissions in line with international commitments. Much UK Government policy is based on modelling present and future emissions using assumptions from SAP, the Standard Assessment Procedure. This paper compares SAP-based modelling against measured gas consumption in 405 dwellings that were monitored in the Energy Follow-Up Survey, an extension of the English Housing Survey. The combined EFUS/EHS provides comprehensive information about space heating energy use for a sample of dwellings: detailed physical data, user behaviour, and measured energy use. Very poor model versus measurement agreement is observed at the individual dwelling level – the average difference is 45%. Much better agreement is observed when applying typical EFUS regimes of 20°C mean demand temperature, 10 hours of heating a day for weekdays and weekends, and a heating season of six months, and comparing average results. Comparisons for the 405 dwellings and an EFUS subset of 1,191 dwellings are both in agreement to within 2%, whilst average 2010 and 2011 sub-national estimates are in agreement to 3% of DUKES figures. The authors recommend changing SAP heating regimes to a mean demand temperature of 20°C, 10 hours of heating a day for weekdays and weekends, and a heating season of six months.
    VL  - 4
    IS  - 2
    ER  - 

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Author Information
  • Cambridge Architectural Research, Cambridge, UK

  • Cambridge Architectural Research, Cambridge, UK

  • Cambridge Architectural Research & Cambridge Energy, Cambridge, UK

  • SBP Ltd, London, UK

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