Skip to main content
SpringerLink
Log in

Operational Characterisation of Neighbourhood Heat Energy After Large-Scale Building Retrofit

  • Conference paper
  • First Online:
Book cover Cold Climate HVAC 2018 (CCC 2018)

Part of the book series: Springer Proceedings in Energy ((SPE))

Included in the following conference series:

  • 1368 Accesses

Abstract

To achieve housing retrofit targets, traditional house-by-house approaches must scale. Neighbourhood retrofit also facilitates community participation. This paper aims to quantitatively characterise the heat energy demand of similar homes in a post-retrofit neighbourhood. The method employs the Modelica AixLib library, dedicated to building performance simulation. A modern semi-detached house is modelled as thermal network. The passive thermal network is calibrated against an equivalent EnergyPlus model. The developed Modelica model then generates time series heat energy demand to meet occupant comfort. This model separates heating for internal space and domestic hot water. Simulation results are gathered for a range of house occupancy profiles, with varying heating schedules and occupant quantities. The calibration results compare the time series of internal house temperature produced by the EnergyPlus and Modelica simulations. Modelica simulations of two heating schedules generate distinct annual demand curves against occupant quantity. As expected in a modern house, domestic hot water accounts for a relatively high proportion of heat energy. Over a year it ranges between 20 and 45% depending on occupant profile. Overall conclusions are threefold. Firstly, occupant profiles of a modern semi-detached house increase annual heat energy demand by 77%, and the coincidence of daily peak demand persists across occupant profiles. Furthermore, percentages of domestic hot water demand start from 20 or 24% and plateau at 39 or 45% depending on space heating schedule. A statistical distribution of energy demand by neighbourhood homes is possible. Its curve plot is not perfectly normal, skewing to larger energy demands.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 219.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. N. Good, L. Zhang, A. Navarro-Espinosa, P. Mancarella, High resolution modelling of multi-energy domestic demand profiles. Appl. Energy 137, 193–210 (2015)

    Article  Google Scholar 

  2. R. Gupta, M. Gregg, S. Passmore, G. Stevens, Intent and outcomes from the retrofit for the future programme: key lessons. Build. Res. Inf. 43, 435–451 (2015)

    Article  Google Scholar 

  3. P. Jones, S. Lannon, J. Patterson, Retrofitting existing housing: how far, how much? Build. Res. Inf. 41, 532–550 (2013)

    Article  Google Scholar 

  4. P. Moran, J. Goggins, M. Hajdukiewicz, Super-insulate or use renewable technology? Life cycle cost, energy and global warming potential analysis of nearly zero energy buildings (NZEB) in a temperate oceanic climate. Energy Build. 139, 590–607 (2017)

    Article  Google Scholar 

  5. B.V. Mathiesen, D. Drysdale, H. Lund, S. Paardekooper, I. Ridjan, D. Connolly, J.S. Jensen, Future Green Buildings (Aalborg University, Department of Development and Planning, Aalborg, 2016)

    Google Scholar 

  6. A. Koch, S. Girard, K. McKoen, Towards a neighbourhood scale for low- or zero-carbon building projects. Build. Res. Inf. 40, 527–537 (2012)

    Article  Google Scholar 

  7. O. Neu, B. Sherlock, S. Oxizidis, D. Flynn, D. Finn, Developing building archetypes for electrical load shifting assessment: analysis of Irish residential stock, in CIBSE ASHRAE Technical Symposium: Moving to a New World of Building Systems Performance, Dublin, Ireland (2014), pp. 1–19

    Google Scholar 

  8. M. Badurek, M. Hanratty, B. Sheldrick, D. Stewart, Building Typology Brochure Ireland (2014)

    Google Scholar 

  9. IEA Annex 60: Summary—IEA EBC Annex 60, http://www.iea-annex60.org/about.html

  10. D. Müller, M. Lauster, A. Constantin, M. Fuchs, P. Remmen, AIXLIB—An open-source Modelica library within the IEA-EBC Annex 60 framework, in BauSIM (2016), pp. 3–6

    Google Scholar 

  11. M. Lauster, J. Teichmann, M. Fuchs, R. Streblow, D. Mueller, Low order thermal network models for dynamic simulations of buildings on city district scale. Build. Environ. 73, 223–231 (2014)

    Article  Google Scholar 

  12. B.D.B. Crawley, L.K. Lawrie, EnergyPlus: energy simulation program. ASHRAE J. 42, 49–56 (2000)

    Google Scholar 

  13. D.B. Crawley, L.K. Lawrie, F.C. Winkelmann, W.F. Buhl, Y.J. Huang, C.O. Pedersen, R.K. Strand, R.J. Liesen, D.E. Fisher, M.J. Witte, J. Glazer, EnergyPlus: creating a new-generation building energy simulation program. Energy Build. 33, 319–331 (2001)

    Article  Google Scholar 

  14. D. Connolly, H. Lund, B.V. Mathiesen, S. Werner, B. Möller, U. Persson, T. Boermans, D. Trier, P.A. Østergaard, S. Nielsen, Heat roadmap Europe: combining district heating with heat savings to decarbonise the EU energy system. Energy Policy 65, 475–489 (2014)

    Article  Google Scholar 

  15. J. Egan, D. Finn, P.H. Deogene Soares, V.A. Rocha Baumann, R. Aghamolaei, P. Beagon, O. Neu, F. Pallonetto, J. O’Donnell, Definition of a useful minimal-set of accurately-specified input data for building energy performance simulation. Energy Build. 165, 172–183 (2018)

    Article  Google Scholar 

  16. A. Garnier, J. Eynard, M. Caussanel, S. Grieu, Predictive control of multizone heating, ventilation and air-conditioning systems in non-residential buildings. Appl. Soft Comput. 37, 847–862 (2015)

    Article  Google Scholar 

  17. A. Tindale, Third-order lumped-parameter simulation method. Build. Serv. Eng. Res. Technol. 14, 87–97 (1993)

    Article  Google Scholar 

  18. NREL: Weather Data by Location EnergyPlus—Europe WMO Region 6, Ireland, https://energyplus.net/weather-location/europe_wmo_region_6/IRL//IRL_Dublin.039690_IWEC

  19. L. Peeters, J. Van der Veken, H. Hens, L. Helsen, W. D’haeseleer, Control of heating systems in residential buildings: current practice. Energy Build. 40, 1446–1455 (2008)

    Article  Google Scholar 

  20. SEAI: What are the electricity factors used in the latest version of DEAP?, http://www.seai.ie/Your_Building/BER/BER_FAQ/FAQ_DEAP/Results/What_are_the_electricity_factors_used_in_the_latest_version_of_DEAP.html

  21. SEAI: Derivation of Primary Energy and CO2 Factors for Electricity in DEAP (2016)

    Google Scholar 

  22. J. Egan, The Definition and Application of a Useful Minimum Set of Accurately-Defined Data for Building Energy Performance Simulation (2015)

    Google Scholar 

  23. B. Coyne, S. Lyons, D. McCoy, The Effects of Home Energy Efficiency Upgrades on Social Housing Tenants: Evidence from Ireland (2016)

    Google Scholar 

  24. J. Salom, A.J. Marszal, J. Widén, J. Candanedo, K.B. Lindberg, Analysis of load match and grid interaction indicators in net zero energy buildings with simulated and monitored data. Appl. Energy 136, 119–131 (2014)

    Article  Google Scholar 

  25. J.P. Waltz, Computerized Building Energy Simulation Handbook (Marcel Dekker, New York, 2000)

    Google Scholar 

Download references

Acknowledgements

Paul Beagon gratefully acknowledges that his research is supported in part by a research grant from Science Foundation Ireland (SFI) under the SFI Strategic Partnership Programme Grant Number SFI/15/SPP/E3125.

Paul thanks Moritz Lauster of RWTH Aachen University and E. ON Energy Research Center, for his kind and useful advice on AixLib library.

Author information

Authors and Affiliations

  1. School of Mechanical and Materials Engineering, University College Dublin, Belfield, 4, Dublin, Ireland

    Paul Beagon & James O’Donnell

  2. Energy Institute, University College Dublin, Belfield, 4, Dublin, Ireland

    Paul Beagon & James O’Donnell

  3. Royal College of Surgeons in Ireland, Lower Mercer Street, 2, Dublin, Ireland

    Fiona Boland

Authors
  1. Paul Beagon
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Fiona Boland
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. James O’Donnell
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Paul Beagon .

Editor information

Editors and Affiliations

  1. Division of Building Services, Lund University, Lund, Sweden

    Dennis Johansson

  2. Division of Building Physics, Lund University, Lund, Sweden

    Hans Bagge

  3. Division of Building Services, Lund University, Lund, Sweden

    Åsa Wahlström

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Beagon, P., Boland, F., O’Donnell, J. (2019). Operational Characterisation of Neighbourhood Heat Energy After Large-Scale Building Retrofit. In: Johansson, D., Bagge, H., Wahlström, Å. (eds) Cold Climate HVAC 2018. CCC 2018. Springer Proceedings in Energy. Springer, Cham. https://doi.org/10.1007/978-3-030-00662-4_19

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-00662-4_19

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-00661-7

  • Online ISBN: 978-3-030-00662-4

  • eBook Packages: EnergyEnergy (R0)

Publish with us

Policies and ethics

Search

Navigation