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Embedding energy flexibility capability in air source heat pumps via third-party control: Insights from a field trial on residential buildings in England

Author

Listed:
  • Turner, P.A.D.
  • Rushby, T.W.
  • Manfren, M.
  • James, P.A.B.
  • Gauthier, S.
  • Bahaj, A.S.
  • Sweetnam, T.
  • Kim, S.
  • Ridett, Ellis

Abstract

This research investigates energy flexibility in residential building clusters transitioning from gas boilers to air source heat pumps, within the broader context of rapid decarbonisation of both building stock and electric grid in the UK. The study field trialed a scalable control approach embedded in heat pumps, as part of the EPSRC funded project "LATENT: Residential heat as an energy system service". The project explores a flexibility paradigm where aggregators and Energy Service Companies (ESCOs) partner with installers and manufacturers to leverage small-scale flexibility sources, to enable swift flexibility deployment in clusters of buildings. Flexibility events were scheduled for ESCO customers in Southern England during typical UK electric grid peak hours, using an intervention and control approach across customer groups. Findings reveal insights into third-party control operation, events duration, override requests, achievable flexibility and user behaviour/comfort preferences. Peak shaving strategies implemented resulted in an average power reduction of 88.2% across events with a maximum demand reduction of 1.581 kW, averaged throughout the cluster of buildings. Override requests occurred in only 2.7% of potential cases, with events lasting from 30 to 120 minutes. The study also assessed temperature dependence in flexibility performance at the cluster level. Results indicate the feasibility of longer energy flexibility events, contingent on a more advanced analysis of technical and social constraints. In conclusion, the research emphasises the significance of conducting field trials to showcase potential for energy flexibility solutions in optimising the operation of electric infrastructure.

Suggested Citation

  • Turner, P.A.D. & Rushby, T.W. & Manfren, M. & James, P.A.B. & Gauthier, S. & Bahaj, A.S. & Sweetnam, T. & Kim, S. & Ridett, Ellis, 2025. "Embedding energy flexibility capability in air source heat pumps via third-party control: Insights from a field trial on residential buildings in England," Applied Energy, Elsevier, vol. 389(C).
  • Handle: RePEc:eee:appene:v:389:y:2025:i:c:s0306261925004350
    DOI: 10.1016/j.apenergy.2025.125705
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    References listed on IDEAS

    as
    1. Tang, Hong & Wang, Shengwei & Li, Hangxin, 2021. "Flexibility categorization, sources, capabilities and technologies for energy-flexible and grid-responsive buildings: State-of-the-art and future perspective," Energy, Elsevier, vol. 219(C).
    2. Mirfin, Anthony & Xiao, Xun & Jack, Michael W., 2024. "TOWST: A physics-informed statistical model for building energy consumption with solar gain," Applied Energy, Elsevier, vol. 369(C).
    3. Le Dréau, J. & Heiselberg, P., 2016. "Energy flexibility of residential buildings using short term heat storage in the thermal mass," Energy, Elsevier, vol. 111(C), pages 991-1002.
    4. Massimiliano Manfren & Karla M. Gonzalez-Carreon & Patrick A. B. James, 2024. "Interpretable Data-Driven Methods for Building Energy Modelling—A Review of Critical Connections and Gaps," Energies, MDPI, vol. 17(4), pages 1-22, February.
    5. Lu, Renzhi & Hong, Seung Ho, 2019. "Incentive-based demand response for smart grid with reinforcement learning and deep neural network," Applied Energy, Elsevier, vol. 236(C), pages 937-949.
    6. Wang, Y. & Wang, J. & He, W., 2022. "Development of efficient, flexible and affordable heat pumps for supporting heat and power decarbonisation in the UK and beyond: Review and perspectives," Renewable and Sustainable Energy Reviews, Elsevier, vol. 154(C).
    7. Massimiliano Manfren & Benedetto Nastasi, 2020. "Parametric Performance Analysis and Energy Model Calibration Workflow Integration—A Scalable Approach for Buildings," Energies, MDPI, vol. 13(3), pages 1-14, February.
    8. Monika Hall & Achim Geissler, 2021. "Comparison of Flexibility Factors and Introduction of A Flexibility Classification Using Advanced Heat Pump Control," Energies, MDPI, vol. 14(24), pages 1-19, December.
    9. Sousa, Joana & Soares, Isabel, 2023. "Benefits and barriers concerning demand response stakeholder value chain: A systematic literature review," Energy, Elsevier, vol. 280(C).
    10. de Wilde, Pieter & Aly, Dalia & Cho, Seongkwon & Kim, Jin-Hong & Kim, Sunghyun & Park, Cheol-Soo, 2025. "Occupant behavioural freedom in building energy use," Applied Energy, Elsevier, vol. 377(PD).
    11. Kathirgamanathan, Anjukan & De Rosa, Mattia & Mangina, Eleni & Finn, Donal P., 2021. "Data-driven predictive control for unlocking building energy flexibility: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).
    12. Julien Lancelot Michellod & Declan Kuch & Christian Winzer & Martin K. Patel & Selin Yilmaz, 2022. "Building Social License for Automated Demand-Side Management—Case Study Research in the Swiss Residential Sector," Energies, MDPI, vol. 15(20), pages 1-25, October.
    13. D’Ettorre, F. & Banaei, M. & Ebrahimy, R. & Pourmousavi, S. Ali & Blomgren, E.M.V. & Kowalski, J. & Bohdanowicz, Z. & Łopaciuk-Gonczaryk, B. & Biele, C. & Madsen, H., 2022. "Exploiting demand-side flexibility: State-of-the-art, open issues and social perspective," Renewable and Sustainable Energy Reviews, Elsevier, vol. 165(C).
    14. Hoicka, Christina E. & Lowitzsch, Jens & Brisbois, Marie Claire & Kumar, Ankit & Ramirez Camargo, Luis, 2021. "Implementing a just renewable energy transition: Policy advice for transposing the new European rules for renewable energy communities," Energy Policy, Elsevier, vol. 156(C).
    15. Ribó-Pérez, David & Heleno, Miguel & Álvarez-Bel, Carlos, 2021. "The flexibility gap: Socioeconomic and geographical factors driving residential flexibility," Energy Policy, Elsevier, vol. 153(C).
    16. Reynders, Glenn & Diriken, Jan & Saelens, Dirk, 2017. "Generic characterization method for energy flexibility: Applied to structural thermal storage in residential buildings," Applied Energy, Elsevier, vol. 198(C), pages 192-202.
    17. Rajavelu Dharani & Madasamy Balasubramonian & Thanikanti Sudhakar Babu & Benedetto Nastasi, 2021. "Load Shifting and Peak Clipping for Reducing Energy Consumption in an Indian University Campus," Energies, MDPI, vol. 14(3), pages 1-16, January.
    18. Wang, Andong & Li, Rongling & You, Shi, 2018. "Development of a data driven approach to explore the energy flexibility potential of building clusters," Applied Energy, Elsevier, vol. 232(C), pages 89-100.
    19. Boßmann, T. & Staffell, I., 2015. "The shape of future electricity demand: Exploring load curves in 2050s Germany and Britain," Energy, Elsevier, vol. 90(P2), pages 1317-1333.
    20. Yan, Xing & Ozturk, Yusuf & Hu, Zechun & Song, Yonghua, 2018. "A review on price-driven residential demand response," Renewable and Sustainable Energy Reviews, Elsevier, vol. 96(C), pages 411-419.
    21. Jenny Crawley & Gemma Moore & Sarah Higginson & Cliff Elwell & Nick Eyre, 2024. "The Role of Domestic Heat Pumps in Providing Flexibility to the UK Electricity System," Energies, MDPI, vol. 17(12), pages 1-15, June.
    22. Papadis, Elisa & Tsatsaronis, George, 2020. "Challenges in the decarbonization of the energy sector," Energy, Elsevier, vol. 205(C).
    23. Markard, Jochen & Hoffmann, Volker H., 2016. "Analysis of complementarities: Framework and examples from the energy transition," Technological Forecasting and Social Change, Elsevier, vol. 111(C), pages 63-75.
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