IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v304y2021ics0306261921010266.html
   My bibliography  Save this article

A multi-zone, fast solving, rapidly reconfigurable building and electrified heating system model for generation of control dependent heat pump power demand profiles

Author

Listed:
  • Johnson, R.C.
  • Royapoor, M.
  • Mayfield, M.

Abstract

The electrification of heating is expected to grow in the UK domestic sector, and this has increased interest in the effects that this may have on low and high voltage network operation. However, Electrified heating profiles that alter with control decisions can only be obtained from dedicated building modelling that energy system modellers do not usually have the expertise to perform, yet these are required for meaningful studies. This work outlines a novel method for modelling air source and ground source heat pump power demand profiles using a multi-zone physics based building modelling framework with building fabric, thermohydraulic, and air flow subsystems. The novel setup framework allows detailed building layout, fabric and control properties to be assigned by analysts with no prior building modelling expertise. Once fully assigned, the building model can be used to generate heat pump power demand profiles at sub minute resolution. Upon testing, a single daily run of the model could be executed in 17 s. The model was then validated against real life test house data, under various control and weather conditions. A small relative error (typically within 10%) was observed between modelled and actual cycle lengths, and modelled and actual heat and electricity demands. Due to its rapid solution rate, the model is of significant value to energy efficiency and distribution network studies, where large demand profile sets that are sensitive to detailed retrofit and control considerations are often essential. The model has been made openly available.

Suggested Citation

  • Johnson, R.C. & Royapoor, M. & Mayfield, M., 2021. "A multi-zone, fast solving, rapidly reconfigurable building and electrified heating system model for generation of control dependent heat pump power demand profiles," Applied Energy, Elsevier, vol. 304(C).
  • Handle: RePEc:eee:appene:v:304:y:2021:i:c:s0306261921010266
    DOI: 10.1016/j.apenergy.2021.117663
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261921010266
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.apenergy.2021.117663?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Aboelsood Zidan & Hossam A. Gabbar, 2016. "DG Mix and Energy Storage Units for Optimal Planning of Self-Sufficient Micro Energy Grids," Energies, MDPI, vol. 9(8), pages 1-18, August.
    2. Wu, Wei & Skye, Harrison M. & Domanski, Piotr A., 2018. "Selecting HVAC systems to achieve comfortable and cost-effective residential net-zero energy buildings," Applied Energy, Elsevier, vol. 212(C), pages 577-591.
    3. Navarro-Espinosa, Alejandro & Mancarella, Pierluigi, 2014. "Probabilistic modeling and assessment of the impact of electric heat pumps on low voltage distribution networks," Applied Energy, Elsevier, vol. 127(C), pages 249-266.
    4. McKenna, Eoghan & Thomson, Murray, 2016. "High-resolution stochastic integrated thermal–electrical domestic demand model," Applied Energy, Elsevier, vol. 165(C), pages 445-461.
    5. Johra, Hicham & Heiselberg, Per, 2017. "Influence of internal thermal mass on the indoor thermal dynamics and integration of phase change materials in furniture for building energy storage: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 19-32.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Love, Jenny & Smith, Andrew Z.P. & Watson, Stephen & Oikonomou, Eleni & Summerfield, Alex & Gleeson, Colin & Biddulph, Phillip & Chiu, Lai Fong & Wingfield, Jez & Martin, Chris & Stone, Andy & Lowe, R, 2017. "The addition of heat pump electricity load profiles to GB electricity demand: Evidence from a heat pump field trial," Applied Energy, Elsevier, vol. 204(C), pages 332-342.
    2. Wang, Zhikun & Crawley, Jenny & Li, Francis G.N. & Lowe, Robert, 2020. "Sizing of district heating systems based on smart meter data: Quantifying the aggregated domestic energy demand and demand diversity in the UK," Energy, Elsevier, vol. 193(C).
    3. Morstyn, Thomas & Collett, Katherine A. & Vijay, Avinash & Deakin, Matthew & Wheeler, Scot & Bhagavathy, Sivapriya M. & Fele, Filiberto & McCulloch, Malcolm D., 2020. "OPEN: An open-source platform for developing smart local energy system applications," Applied Energy, Elsevier, vol. 275(C).
    4. Yi, Ji Hyun & Ko, Woong & Park, Jong-Keun & Park, Hyeongon, 2018. "Impact of carbon emission constraint on design of small scale multi-energy system," Energy, Elsevier, vol. 161(C), pages 792-808.
    5. Reilly, Aidan & Kinnane, Oliver, 2017. "The impact of thermal mass on building energy consumption," Applied Energy, Elsevier, vol. 198(C), pages 108-121.
    6. Hai Lu & Jiaquan Yang & Kari Alanne, 2018. "Energy Quality Management for a Micro Energy Network Integrated with Renewables in a Tourist Area: A Chinese Case Study," Energies, MDPI, vol. 11(4), pages 1-24, April.
    7. Lizana, Jesus & Friedrich, Daniel & Renaldi, Renaldi & Chacartegui, Ricardo, 2018. "Energy flexible building through smart demand-side management and latent heat storage," Applied Energy, Elsevier, vol. 230(C), pages 471-485.
    8. Yang, Ting & Zhao, Liyuan & Li, Wei & Zomaya, Albert Y., 2021. "Dynamic energy dispatch strategy for integrated energy system based on improved deep reinforcement learning," Energy, Elsevier, vol. 235(C).
    9. Dong, Lijun & Kang, Xiaojun & Pan, Mengqi & Zhao, Man & Zhang, Feng & Yao, Hong, 2020. "B-matching-based optimization model for energy allocation in sea surface monitoring," Energy, Elsevier, vol. 192(C).
    10. Fraga, Carolina & Hollmuller, Pierre & Schneider, Stefan & Lachal, Bernard, 2018. "Heat pump systems for multifamily buildings: Potential and constraints of several heat sources for diverse building demands," Applied Energy, Elsevier, vol. 225(C), pages 1033-1053.
    11. Yunusov, Timur & Torriti, Jacopo, 2021. "Distributional effects of Time of Use tariffs based on electricity demand and time use," Energy Policy, Elsevier, vol. 156(C).
    12. Protopapadaki, Christina & Saelens, Dirk, 2017. "Heat pump and PV impact on residential low-voltage distribution grids as a function of building and district properties," Applied Energy, Elsevier, vol. 192(C), pages 268-281.
    13. Yanjuan Yu & Hongkun Chen & Lei Chen, 2018. "Comparative Study of Electric Energy Storages and Thermal Energy Auxiliaries for Improving Wind Power Integration in the Cogeneration System," Energies, MDPI, vol. 11(2), pages 1-16, January.
    14. Li, Weilin & Jing, Mingyi & Li, Rufei & Gao, Junxi & Zhu, Jiayin & Li, Ruixin, 2023. "Study of the optimal placement of phase change materials in existing buildings for cooling load reduction - Take the Central Plain of China as an example," Renewable Energy, Elsevier, vol. 209(C), pages 71-84.
    15. Lombardi, Francesco & Balderrama, Sergio & Quoilin, Sylvain & Colombo, Emanuela, 2019. "Generating high-resolution multi-energy load profiles for remote areas with an open-source stochastic model," Energy, Elsevier, vol. 177(C), pages 433-444.
    16. Thomas, Dimitrios & D’Hoop, Gaspard & Deblecker, Olivier & Genikomsakis, Konstantinos N. & Ioakimidis, Christos S., 2020. "An integrated tool for optimal energy scheduling and power quality improvement of a microgrid under multiple demand response schemes," Applied Energy, Elsevier, vol. 260(C).
    17. Fuentes, E. & Arce, L. & Salom, J., 2018. "A review of domestic hot water consumption profiles for application in systems and buildings energy performance analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 1530-1547.
    18. Erdinç, Fatma Gülşen, 2023. "Rolling horizon optimization based real-time energy management of a residential neighborhood considering PV and ESS usage fairness," Applied Energy, Elsevier, vol. 344(C).
    19. Manuel S. Alvarez-Alvarado & Johnny Rengifo & Rommel M. Gallegos-Núñez & José G. Rivera-Mora & Holguer H. Noriega & Washington Velasquez & Daniel L. Donaldson & Carlos D. Rodríguez-Gallegos, 2022. "Particle Swarm Optimization for Optimal Frequency Response with High Penetration of Photovoltaic and Wind Generation," Energies, MDPI, vol. 15(22), pages 1-12, November.
    20. Yuehong Lu & Mohammed Alghassab & Manuel S. Alvarez-Alvarado & Hasan Gunduz & Zafar A. Khan & Muhammad Imran, 2020. "Optimal Distribution of Renewable Energy Systems Considering Aging and Long-Term Weather Effect in Net-Zero Energy Building Design," Sustainability, MDPI, vol. 12(14), pages 1-20, July.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:appene:v:304:y:2021:i:c:s0306261921010266. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.