Building Energy Simulation of Traditional Listed Dwellings in the UK: Data Sourcing for a Base-Case Model

  • Michela MenconiEmail author
  • Noel Painting
  • Poorang Piroozfar
Conference paper
Part of the Smart Innovation, Systems and Technologies book series (SIST, volume 163)


The need for improving energy efficiency and reducing carbon emissions has made retrofitting existing homes a priority today. A research project has been designed with one of its aims to propose a framework to intervene in traditional listed dwellings (TLDs) to reduce their environmental impact in England, with a special focus on South-East region. Selected case studies in the City of Brighton and Hove, have been modelled and simulated in their status quo using Dynamic Energy Simulation (DES). The models, calibrated using monitored energy and indoor conditions data, are then to be used to simulate the effect of permissible retrofit interventions. DES requires accurate sourcing of multiple input data, to ensure that the models created, closely resemble the real case study dwellings in their energy performance and thermal behaviour. This process can be extremely challenging in the case of simulation of TLDs, where most of the envelope’s construction is unknown and intrusive tests are not usually permitted. The data sourcing process is even more complex in the case of dwellings in use, because of the variability of occupancy profiles and patterns of use over time. Providing a brief overview of the methodology adopted in this study, this paper describes, in detail, the approach devised to ensure that the most credible datasets are collected from different sources for generating models that accurately represent the real case study dwellings in their status quo and can be used in the following stages of the analysis to asses potential retrofit interventions.


Building energy simulation Traditional listed dwellings Base-case model Dynamic energy modelling Responsive retrofit 


  1. 1.
    Fesanghary, M., Asadi, S., Geem, Z.W.: Design of low-emission and energy-efficient residential buildings using a multi-objective optimization algorithm. Build. Environ. 49, 245 (2012)CrossRefGoogle Scholar
  2. 2.
    Garber, R.: Optimisation stories: the impact of building information modelling on contemporary design practice. Architect. Design 79, 6–13 (2009)CrossRefGoogle Scholar
  3. 3.
    Nguyen, A.-T., Reiter, S., Rigo, P.: A review on simulation-based optimization methods applied to building performance analysis. Appl. Energy 113, 1043–1058 (2014)CrossRefGoogle Scholar
  4. 4.
    Wang, W., Rivard, H., Zmeureanu, R.: An object-oriented framework for simulation-based green building design optimization with genetic algorithms. Adv. Eng. Inform. 19, 5–23 (2005)CrossRefGoogle Scholar
  5. 5.
    Ascione, F., Bianco, N., De Masi, R.F., De’Rossi, F., Vanoli, G.P.: Energy retrofit of an educational building in the ancient center of Benevento. Feasibility study of energy savings and respect of the historical value. Energy Build. 95, 172–183 (2015)CrossRefGoogle Scholar
  6. 6.
    Kolaitis, D.I., Malliotakis, E., Kontogeorgos, D.A., Mandilaras, I., Karsourinis, D.I., Founti, M.A.: Comparative assessment of internal and external thermal insulation systems for energy efficient retrofitting of residential buildings. Energy Build. 64, 123–131 (2013)CrossRefGoogle Scholar
  7. 7.
    Pernigotto, G., Penna, P., Cappelletti, F., Gasparella, A.: Extensive Utilization Of Dynamic Simulation For Sensitivity Analysis And Optimization Design Of Refurbishment Measures. International High Performance Buildings Conference. Purdue (2012)Google Scholar
  8. 8.
    Stazi, F., Veglio, A., Di Perna, C., Munafo, P.: Experimental comparison between 3 different traditional wall constructions and dynamic simulations to identify optimal thermal insulation strategies. Energy Build. 60, 429–441 (2013)CrossRefGoogle Scholar
  9. 9.
    Yang, Z., Becerik-Gerber, B.: A model calibration framework for simultaneous multi-level building energy simulation. Appl. Energy 149, 415–431 (2015)CrossRefGoogle Scholar
  10. 10.
    Wei, S., Wang, W., Jones, R., De Wilde, P.: Using building performance simulation to save residential space heating energy: A pilot testing. 8th Windsor Conference: Counting the Cost of Comfort in a changing world, 10–13 April 2014 Cumberland Lodge, Windsor, UK. London: Network for Comfort and Energy Use in Buildings (2014)Google Scholar
  11. 11.
    Diakaki, C., Grigoroudis, E., Kolokotsa, D.: Performance study of a multi-objective mathematical programming modelling approach for energy decision-making in buildings. Energy 59, 534–542 (2013)CrossRefGoogle Scholar
  12. 12.
    Barnham, B., Heath, N., Pearson, G.: Historic Scotland Technical Paper 3: Energy Modelling Analysis of a Scottish Tenement Flat. Historic Scotland, Edinburgh (2008)Google Scholar
  13. 13.
    Heath, N., Pearson, G., Barnham, B., Atkins, R.: Historic Scotland Technical Paper 8: Energy modelling of the Garden Bothy, Dumfries House. Historic Scotland, Edinburgh (2010)Google Scholar
  14. 14.
    Ingram, V., Jenkins, D.: Historic Scotland Technical Paper 18: Evaluating energy modelling for traditionally constructed dwellings. Historic Scotland, Edinburgh (2013)Google Scholar
  15. 15.
    STBA: Responsible Retrofit of Traditional Buildings [Online]. Available:, last accessed 2017/7/20. Sustainable Traditional Buildings Alliance (2012a)
  16. 16.
    IES: ModelIT: Model builder User Guide., last accessed 2017/1/11. IES (2016)
  17. 17.
    McNally, Y.: An investigation into energy saving via retrofit compared to replacement housing. Ph.D., Ulster University (2014)Google Scholar
  18. 18.
    Memon, S.: Analysing the potential of retrofitting ultra-low heat loss triple vacuum glazed windows to an existing UK solid wall dwelling. International Journal of Renewable Energy Development (IJRED) 3, 161–174 (2014)Google Scholar
  19. 19.
    Pomponi, F. & Piroozfar, P.: Double skin façade (DSF) technologies for UK office refurbishments: a systemic matchmaking practice (2015)Google Scholar
  20. 20.
    Flores, J.A.M.: The investigation of energy efficiency measures in traditional buildings in the Oporto World Heritage Site. Oxford Brookes University, PhD (2013)Google Scholar
  21. 21.
    Ingram, V.: Energy performance of traditionally constructed dwellings in Scotland. PhD, Heriot-Watt University (2013)Google Scholar
  22. 22.
    Moran, F.: Benchmarking the energy use of historic dwellings in Bath and the role for retrofit and LZC technologies to reduce CO2 emissions. Doctor of Philosophy, University of Bath (2013)Google Scholar
  23. 23.
    IES: Construct DXF: DXF Drawing Requirements [Online]. Available:, last accessed 2017/1/6. IES (2015c)
  24. 24.
    IES: Integrated Environmental Solutions [Online]. Available:, last accessed 2016/10/13. IES (2018a)
  25. 25.
    ASHRAE: ASHRAE Guideline 14-2002 for Measurement of Energy and Demand Savings. American Society of Heating, Refrigerating and Air-conditioning Engineers, Atlanta, GA (2002)Google Scholar
  26. 26.
    IES: MacroFlo Calculation Methods [Online]. Available:, last accessed 2017/4/15. IES (2015d)
  27. 27.
    IES: MacroFlo User Guide [Online]. Available:, last accessed 2016/1/10. IES (2015e)
  28. 28.
    IES: Tabular Building Template Manager (BTM) User Guide [Online]. Available:, last accessed 2017/1/18. IES (2015f)
  29. 29.
    IES: BTM User Guide—Building Template Manager [Online]. Available:, last accessed 2017/1/11. IES (2017)
  30. 30.
    Historic England: Listed Buildings. Last accessed 20 Nov 2018
  31. 31.
    BS EN ISO 10456: Building materials and products. Hygrothermal properties. Tabulated design values and procedures for determining declared and design thermal values (2007)Google Scholar
  32. 32.
    CIBSE: CIBSE guide A: Environmental Design. Chartered Institution of Building Services Engineers, London (2015)Google Scholar
  33. 33.
    Černy, R., Kunca, A., Tydlitat, V., Drchalova, J., Rovnanikova, P.: Effect of pozzolanic admixtures on mechanical, thermal and hygric properties of lime plasters. Constr. Build. Mater. 20, 849–857 (2006)CrossRefGoogle Scholar
  34. 34.
    Theodoridou, M., Kyriakou, L., Ioannou, I.: PCM-enhanced Lime Plasters for Vernacular and Contemporary Architecture. Energy Procedia 97, 539–545 (2016)CrossRefGoogle Scholar
  35. 35.
    Vejmelkova, E., Keppert, M., Kersner, Z., Rovnikova, P., Černy, R.: Mechanical, fracture-mechanical, hydric, thermal, and durability properties of lime–metakaolin plasters for renovation of historical buildings. Constr. Build. Mater. 31, 22–28 (2012)CrossRefGoogle Scholar
  36. 36.
    IES: Historic Scotland Technical Paper 5: Energy modelling of a mid19th century villa—Baseline performance and improvement options. Edinburgh: Historic Scotland (2009)Google Scholar
  37. 37.
    Wood, C., Bordass, B., Baker, P.: Research into the thermal performance of traditional windows: timber sash windows. English Heritage (2009)Google Scholar
  38. 38.
    IES: Apache-Tables User Guide., last accessed 2017/1/2. IES (2015b)
  39. 39.
    Baker, P.: Historic Scotland Technical Paper 1: thermal performance of traditional windows. Historic Scotland, Edinburgh (2008)Google Scholar
  40. 40.
    Pickles, D.: Energy Efficiency and Historic Buildings: Draught-proofing Windows and Doors. Historic England, London (2016)Google Scholar
  41. 41.
    Porritt, S., Shao, L., Cropper, P., Goodier, C.: Adapting dwellings for heat waves. Sustain. Cities Soc. 1, 81–90 (2011)CrossRefGoogle Scholar
  42. 42.
    IES: Tabular Room Data User Guide [Online]. Available:, last accessed 2017/1/14. IES (2015 g)
  43. 43.
    EST: Measurement of domestic hot water consumption in dwellings. Energy Saving Trust (2008)Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  • Michela Menconi
    • 1
    Email author
  • Noel Painting
    • 1
  • Poorang Piroozfar
    • 1
    • 2
  1. 1.School of Environment and TechnologyUniversity of BrightonBrightonUK
  2. 2.Digital Construction LabUniversity of BrightonBrightonUK

Personalised recommendations