Rees, S orcid.org/0000-0003-4869-1632 and Van Lysebetten, G (2020) A response factor approach to modelling long-term thermal behaviour of energy piles. Computers and Geotechnics, 120. 103424. ISSN 0266-352X
Abstract
Predicting the long-term thermal performance of an energy pile ground heat exchanger system requires a computationally efficient model that captures the three-dimensional features and interacting thermal boundary conditions found in such systems. We present a model that employs a response factor approach to predicting long-term thermal behaviour based on a Dynamic Thermal Network representation. This allows fully three-dimensional geometric representation of the problem and application of boundary conditions at the ground and building sub-surfaces in addition to the pipes. The model has been validated using data from long-term monitoring of a pile in Belgium excited by a combination of heating and cooling demands in a range of environmental conditions. We further demonstrate application of the model to simulated annual building energy demands and the significance of treatment of the upper surface boundary conditions. The model is shown to be capable of representing building system and environmental conditions effectively and furthermore computationally efficient enough for routine design and simulation tasks.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2020 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/BY-NC-ND/4.0/). |
Keywords: | Geothermal energy; Ground heat exchanger; Energy pile; Thermal performance; Model validation |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Civil Engineering (Leeds) |
Funding Information: | Funder Grant number EU - European Union 656889 |
Depositing User: | Symplectic Publications |
Date Deposited: | 09 Jan 2020 12:55 |
Last Modified: | 12 Feb 2020 15:30 |
Status: | Published |
Publisher: | Elsevier |
Identification Number: | 10.1016/j.compgeo.2019.103424 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:155435 |