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Comparative Analysis of Methods for Predicting Brine Temperature in Vertical Ground Heat Exchanger—A Case Study

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  • Joanna Piotrowska-Woroniak

    (Heating, Ventilation and Air Conditioning Department, Bialystok University of Technology, Wiejska 45E, 15-351 Bialystok, Poland)

  • Krzysztof Nęcka

    (Faculty of Production and Power Engineering, University of Agriculture, Balicka 116 B, 30-149 Krakow, Poland)

  • Tomasz Szul

    (Faculty of Production and Power Engineering, University of Agriculture, Balicka 116 B, 30-149 Krakow, Poland)

  • Stanisław Lis

    (Faculty of Production and Power Engineering, University of Agriculture, Balicka 116 B, 30-149 Krakow, Poland)

Abstract

This research was carried out to compare selected forecasting methods, such as the following: Artificial Neural Networks (ANNs), Classification and Regression Trees (CARTs), Chi-squared Automatic Interaction Detector (CHAID), Fuzzy Logic Toolbox (FUZZY), Multivariant Adaptive Regression Splines (MARSs), Regression Trees (RTs), Rough Set Theory (RST), and Support Regression Trees (SRTs), in the context of determining the temperature of brine from vertical ground heat exchangers used by a heat pump heating system. The subject of the analysis was a public building located in Poland, in a temperate continental climate zone. The results of this study indicate that the models based on Rough Set Theory (RST) and Artificial Neural Networks (ANNs) achieved the highest accuracy in predicting brine temperature, with the choice of the preferred method depending on the input variables used for modeling. Using three independent variables (mean outdoor air temperature, month of the heating season, mean solar irradiance), Rough Set Theory (RST) was one of the best models, for which the evaluation rates were as follows: CV RMSE 21.6%, MAE 0.3 °C, MAPE 14.3%, MBE 3.1%, and R 2 0.96. By including an additional variable (brine flow rate), Artificial Neural Networks (ANNs) achieved the most accurate predictions. They had the following evaluation rates: CV RMSE 4.6%, MAE 0.05 °C, MAPE 1.7%, MBE 0.4%, and R 2 0.99.

Suggested Citation

  • Joanna Piotrowska-Woroniak & Krzysztof Nęcka & Tomasz Szul & Stanisław Lis, 2024. "Comparative Analysis of Methods for Predicting Brine Temperature in Vertical Ground Heat Exchanger—A Case Study," Energies, MDPI, vol. 17(6), pages 1-13, March.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:6:p:1465-:d:1359435
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    References listed on IDEAS

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    4. Joanna Piotrowska-Woroniak & Tomasz Szul & Grzegorz Woroniak, 2023. "Application of a Model Based on Rough Set Theory (RST) for Estimating the Temperature of Brine from Vertical Ground Heat Exchangers (VGHE) Operated with a Heat Pump—A Case Study," Energies, MDPI, vol. 16(20), pages 1-12, October.
    5. Kerme, Esa Dube & Fung, Alan S., 2020. "Heat transfer simulation, analysis and performance study of single U-tube borehole heat exchanger," Renewable Energy, Elsevier, vol. 145(C), pages 1430-1448.
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