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Fluid temperature predictions of geothermal borefields using load estimations via state observers

Iago Cupeiro Figueroa, Massimo Cimmino, Ján Drgoňa and Lieve Helsen

Article (2021)

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Cite this document: Figueroa, I. C., Cimmino, M., Drgoňa, J. & Helsen, L. (2021). Fluid temperature predictions of geothermal borefields using load estimations via state observers. Journal of Building Performance Simulation, 14(1). doi:10.1080/19401493.2020.1838612
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Abstract

Fluid temperature predictions of geothermal borefields usually involve temporal superposition of its characteristic g-function, using load aggregation schemes to reduce computational times. Assuming that the ground has linear properties, it can be modelled as a linear state-space system where the states are the aggregated loads. However, the application and accuracy of these models is compromised when the borefield is already operating and its load history is not registered or there are gaps in the data. This paper assesses the performance of state observers to estimate the borefield load history to obtain accurate fluid predictions. Results show that both Time-Varying Kalman Filter (TVKF) and Moving Horizon Estimator (MHE) provide predictions with average and maximum errors below 0.1∘C and 1∘C, respectively. MHE outperforms TVKF in terms of n-step ahead output predictions and load history profile estimates at the expense of about five times more computational time.

Uncontrolled Keywords

Geothermal modelling, fluid temperature prediction, load estimation, state observers, Kalman filter, moving horizon estimation

Open Access document in PolyPublie
Subjects: 2100 Génie mécanique > 2100 Génie mécanique
2200 Mécanique des fluides > 2200 Mécanique des fluides
Department: Département de génie mécanique
Research Center: Non applicable
Funders: EU - H2020-EE-2016-RIA-IA programme in Hybrid Low Grade Thermal Energy Systems - Hybrid MPC GEOTABS’
Grant number: 723649
Date Deposited: 14 Dec 2020 10:16
Last Modified: 05 Nov 2021 01:15
PolyPublie URL: https://publications.polymtl.ca/5505/
Document issued by the official publisher
Journal Title: Journal of Building Performance Simulation (vol. 14, no. 1)
Publisher: Taylor & Francis
Official URL: https://doi.org/10.1080/19401493.2020.1838612

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