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Application of a Model Based on Rough Set Theory (RST) to Estimate the Energy Efficiency of Public Buildings

Author

Listed:
  • Joanna Piotrowska-Woroniak

    (HVAC Department, Bialystok University of Technology, Wiejska 45E, 15-351 Bialystok, Poland)

  • Tomasz Szul

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

Abstract

The study was carried out on a group of 85 public buildings, which differed in type of use, construction technology and heating systems. From the collected data, a set of qualitative and quantitative variables characterizing them in terms of heat demand was extracted. In this paper, the authors undertook to test the suitability of a model based on rough set theory (RST), which allows the analysis of imprecise, general and uncertain data. To obtain input data for the RST model in quantitative form, the authors used an alternative approach, which is a method based on the thermal properties of buildings. The quality of the predictive model was evaluated based on the following indicators, such as the coefficient of determination (R 2 ), the mean bias error (MBE), the coefficient of variance of the root mean square error (CV RMSE) and the mean absolute percentage error (MAPE), which are accepted as statistical calibration standards by ASHRAE (American Society of Heating, Refrigerating and Air-Conditioning Engineers). A quality-acceptable predictive model must meet the calibration conditions: MBE ±5%, CV RMSE < 15% and R 2 > 0.75. For the analyzed RST model, the following values of evaluation indicators were obtained: MBE = −1.1%, CV RMSE = 11.8% and R 2 = 0.91. The evaluation results obtained gave rise to the conclusion that the method used, which is based on a limited amount of data describing buildings, gives good results in estimating the unit rate of energy demand for heating.

Suggested Citation

  • Joanna Piotrowska-Woroniak & Tomasz Szul, 2022. "Application of a Model Based on Rough Set Theory (RST) to Estimate the Energy Efficiency of Public Buildings," Energies, MDPI, vol. 15(23), pages 1-13, November.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:23:p:8793-:d:980364
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    References listed on IDEAS

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    1. Beata Sadowska & Joanna Piotrowska-Woroniak & Grzegorz Woroniak & Wiesław Sarosiek, 2022. "Energy and Economic Efficiency of the Thermomodernization of an Educational Building and Reduction of Pollutant Emissions—A Case Study," Energies, MDPI, vol. 15(8), pages 1-31, April.
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    3. Joanna Piotrowska-Woroniak & Krzysztof Cieśliński & Grzegorz Woroniak & Jonas Bielskus, 2022. "The Impact of Thermo-Modernization and Forecast Regulation on the Reduction of Thermal Energy Consumption and Reduction of Pollutant Emissions into the Atmosphere on the Example of Prefabricated Build," Energies, MDPI, vol. 15(8), pages 1-32, April.
    4. Joanna Piotrowska-Woroniak, 2021. "Determination of the Selected Wells Operational Power with Borehole Heat Exchangers Operating in Real Conditions, Based on Experimental Tests," Energies, MDPI, vol. 14(9), pages 1-21, April.
    5. Tomasz Szul & Krzysztof Nęcka & Stanisław Lis, 2021. "Application of the Takagi-Sugeno Fuzzy Modeling to Forecast Energy Efficiency in Real Buildings Undergoing Thermal Improvement," Energies, MDPI, vol. 14(7), pages 1-16, March.
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    9. Tomasz Szul & Stanisław Kokoszka, 2020. "Application of Rough Set Theory (RST) to Forecast Energy Consumption in Buildings Undergoing Thermal Modernization," Energies, MDPI, vol. 13(6), pages 1-17, March.
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    11. Tomasz Szul & Krzysztof Nęcka & Thomas G. Mathia, 2020. "Neural Methods Comparison for Prediction of Heating Energy Based on Few Hundreds Enhanced Buildings in Four Season’s Climate," Energies, MDPI, vol. 13(20), pages 1-17, October.
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    Cited by:

    1. Piotr Michalak & Krzysztof Szczotka & Jakub Szymiczek, 2023. "Audit-Based Energy Performance Analysis of Multifamily Buildings in South-East Poland," Energies, MDPI, vol. 16(12), pages 1-21, June.
    2. 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.

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