Lean and interpretable digital twins for building energy monitoring – a case study with smart thermostatic radiator valves and gas absorption heat pumps
Lean and interpretable digital twins for building energy monitoring – a case study with smart thermostatic radiator valves and gas absorption heat pumps
The transition to low carbon energy systems poses challenges in terms of energy efficiency. In building refurbishment projects, efficient technologies such as smart controls and heat pumps are increasingly being used as a substitute for conventional technologies with the aim of reducing carbon emissions and determining operational energy and cost savings, together with other benefits. Measured building performance, however, often reveals a significant gap between the predicted energy use (design stage) and actual energy use (operation stage). For this reason, lean and interpretable digital twins are needed for building energy monitoring aimed at persistence of savings and continuous performance improvement. In this research, interpretable regression models are built with data at multiple temporal resolutions (monthly, daily and hourly) and seamlessly integrated with the goal of verifying the performance improvements due to Smart thermostatic radiator valves (TRVs) and gas absorption heat pumps (GAHPs) as well as giving insights on the performance of the building as a whole. Further, as part of modelling research, time of week and temperature (TOWT) approach is reformulated and benchmarked against its original implementation. The case study chosen is Hale Court sheltered housing, located in the city of Portsmouth (UK). This building has been used for the field-testing of innovative technologies such as TRVs and GAHPs within the EU Horizon 2020 project THERMOSS. The results obtained are used to illustrate possible extensions of the use of energy signature modelling, highlighting implications for energy management and innovative building technologies development.
Data-driven methods, Digital twins, Energy Analytics, Energy management, Energy signature, Gas absorption heat pumps, Thermostatic radiator valves
Manfren, Massimiliano
f2b8c02d-cb78-411d-aed1-c4d056365392
James, Patrick A.B.
da0be14a-aa63-46a7-8646-a37f9a02a71b
Aragon, Victoria
f2a397a1-9d24-4f68-8f22-cc3270761d82
Tronchin, Lamberto
8527a327-51fb-4865-b99d-eab721dadec9
26 September 2023
Manfren, Massimiliano
f2b8c02d-cb78-411d-aed1-c4d056365392
James, Patrick A.B.
da0be14a-aa63-46a7-8646-a37f9a02a71b
Aragon, Victoria
f2a397a1-9d24-4f68-8f22-cc3270761d82
Tronchin, Lamberto
8527a327-51fb-4865-b99d-eab721dadec9
Manfren, Massimiliano, James, Patrick A.B., Aragon, Victoria and Tronchin, Lamberto
(2023)
Lean and interpretable digital twins for building energy monitoring – a case study with smart thermostatic radiator valves and gas absorption heat pumps.
Energy and AI, 14, [100304].
(doi:10.1016/j.egyai.2023.100304).
Abstract
The transition to low carbon energy systems poses challenges in terms of energy efficiency. In building refurbishment projects, efficient technologies such as smart controls and heat pumps are increasingly being used as a substitute for conventional technologies with the aim of reducing carbon emissions and determining operational energy and cost savings, together with other benefits. Measured building performance, however, often reveals a significant gap between the predicted energy use (design stage) and actual energy use (operation stage). For this reason, lean and interpretable digital twins are needed for building energy monitoring aimed at persistence of savings and continuous performance improvement. In this research, interpretable regression models are built with data at multiple temporal resolutions (monthly, daily and hourly) and seamlessly integrated with the goal of verifying the performance improvements due to Smart thermostatic radiator valves (TRVs) and gas absorption heat pumps (GAHPs) as well as giving insights on the performance of the building as a whole. Further, as part of modelling research, time of week and temperature (TOWT) approach is reformulated and benchmarked against its original implementation. The case study chosen is Hale Court sheltered housing, located in the city of Portsmouth (UK). This building has been used for the field-testing of innovative technologies such as TRVs and GAHPs within the EU Horizon 2020 project THERMOSS. The results obtained are used to illustrate possible extensions of the use of energy signature modelling, highlighting implications for energy management and innovative building technologies development.
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e-pub ahead of print date: 26 September 2023
Published date: 26 September 2023
Additional Information:
Funding Information:
This study and project is financially supported by EU Research and Innovation programme Horizon 2020 through number 723562 – THERMOSS. The authors would like to thank the European Commission to enable the funding of this project.
Keywords:
Data-driven methods, Digital twins, Energy Analytics, Energy management, Energy signature, Gas absorption heat pumps, Thermostatic radiator valves
Identifiers
Local EPrints ID: 483227
URI: http://eprints.soton.ac.uk/id/eprint/483227
ISSN: 2666-5468
PURE UUID: b87b514d-341e-4870-aa78-a77244647df0
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Date deposited: 26 Oct 2023 16:48
Last modified: 06 Jun 2024 01:59
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Author:
Lamberto Tronchin
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