Publication Type

Journal Article

Publication Date (Issue Year)

2024

Journal Name

Case Studies in Thermal Engineering

Abstract

This study employs an inverse grey-box (IGB) modeling approach, which combines measured data and the physics of systems to predict the performance of shallow underground thermal en- ergy storage (UTES) with top and side insulation. A simplified IGB model of the shallow UTES was developed using thermal network analysis. Experimental studies were conducted for shallow vertical and horizontal UTES configurations. Detailed models representing the field experiments were developed using the TRNSYS simulation tool and calibrated with the measured data from the experimental setup. The 4 Resistance 2 Capacitance (4R2C) IGB model was trained and tested in MATLAB using field experimental data and the data from the calibrated TRNSYS model. In comparing experimental data with the TRNSYS model for UTES, the prediction of outlet water temperature showed good agreement, with root mean square error (RMSE) and coefficient of variation of RMSE (CVRMSE) values of 0.94 °C and 3.16 % for vertical, and 0.99 °C and 2.97 % for horizontal configurations. The IGB model also aligned well with the experimental data, show- ing CVRMSE of 7.91 % and 3.17 % for vertical and horizontal systems, respectively. Sensitivity analysis revealed that model performance improves with longer training durations and closer testing times to training periods. However, a convergence point of 20 weeks of training data was achieved for making long-term performance predictions

Keywords

Shallow underground thermal storage, Inverse grey-box model, Model calibration, Experimental data, Simulated data, Training and testing

Rsif Scholar Name

Fabian Chidubem Eze

Rsif Scholar Nationality

Nigeria

Cohort

Cohort 2

Thematic Area

Energy including Renewables

Africa Host University (AHU)

University of Nairobi (UoN), Kenya

Funding Statement

This work was supported by the Korea Institute of Energy Technology Evaluation Planning (KETEP) through the research project “Innovative Energy Remodeling Total Technologies for the Aging Public Buildings (No. 20202020800360)” and the Partnership for Skills in Applied Sciences Engineering and Technology – Regional Scholarship and Innovation Fund (PASET-RSIF) by International Center of Insect Physiology and Ecology (ICIPE).

Share

COinS
 
 

To view the content in your browser, please download Adobe Reader or, alternately,
you may Download the file to your hard drive.

NOTE: The latest versions of Adobe Reader do not support viewing PDF files within Firefox on Mac OS and if you are using a modern (Intel) Mac, there is no official plugin for viewing PDF files within the browser window.