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Simulation of a Building with Hourly and Daily Varying Ventilation Flow: An Application of the Simulink S-Function

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  • Piotr Michalak

    (Faculty of Mechanical Engineering and Robotics, AGH University of Science and Technology, Mickiewicza 30, 30-059 Kraków, Poland)

Abstract

This paper presents an application of the Simulink stvmgain S-function for the thermal modelling of a building zone based on the resistance–capacitance scheme of EN ISO 13790. That model in the form of the state-space matrix with time-varying elements was used in simulations of a building with hourly and, suggested in that standard, daily averaged ventilation airflow in five European cities. The following two ventilation schedules were used: occupancy-based; and wind-dependent. Comparative simulations were conducted in EnergyPlus. In general, the results obtained for the annual heating and cooling demand were better for hourly than daily averaged ventilation with an error below 10%. However, in several cases of cooling, the error was above 30%. When considering hourly indoor air temperatures, the proposed method provided very good results with MAE of up to 0.52 °C and 0.46 °C, RMSE < 0.69 °C and 0.62 °C, and CV(RMSE) < 3.09% and 2.75% for the daily averaged and hourly ventilation flow, respectively. For wind-driven ventilation, the temperatures were as follows: MAE < 0.49 °C and 0.48 °C; RMSE < 0.69 °C and 0.68 °C; and CV(RMSE) < 3.01% and 2.97%.

Suggested Citation

  • Piotr Michalak, 2023. "Simulation of a Building with Hourly and Daily Varying Ventilation Flow: An Application of the Simulink S-Function," Energies, MDPI, vol. 16(24), pages 1-25, December.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:24:p:7958-:d:1296094
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    References listed on IDEAS

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    1. Anna Barwińska-Małajowicz & Radosław Pyrek & Krzysztof Szczotka & Jakub Szymiczek & Teresa Piecuch, 2023. "Improving the Energy Efficiency of Public Utility Buildings in Poland through Thermomodernization and Renewable Energy Sources—A Case Study," Energies, MDPI, vol. 16(10), pages 1-21, May.
    2. Ibrahim M. Kadad & Ashraf A. Ramadan & Kandil M. Kandil & Adel A. Ghoneim, 2022. "Relationship between Ultraviolet-B Radiation and Broadband Solar Radiation under All Sky Conditions in Kuwait Hot Climate," Energies, MDPI, vol. 15(9), pages 1-19, April.
    3. Piotr Michalak, 2023. "Simulation and Experimental Study on the Use of Ventilation Air for Space Heating of a Room in a Low-Energy Building," Energies, MDPI, vol. 16(8), pages 1-17, April.
    4. Abdel-Aal, R.E. & Elhadidy, M.A. & Shaahid, S.M., 2009. "Modeling and forecasting the mean hourly wind speed time series using GMDH-based abductive networks," Renewable Energy, Elsevier, vol. 34(7), pages 1686-1699.
    5. Buonomano, A. & Forzano, C. & Kalogirou, S.A. & Palombo, A., 2019. "Building-façade integrated solar thermal collectors: Energy-economic performance and indoor comfort simulation model of a water based prototype for heating, cooling, and DHW production," Renewable Energy, Elsevier, vol. 137(C), pages 20-36.
    6. Krzysztof Szczotka & Anna Barwińska-Małajowicz & Jakub Szymiczek & Radosław Pyrek, 2023. "Thermomodernization as a Mechanism for Improving Energy Efficiency and Reducing Emissions of Pollutants into the Atmosphere in a Public Utility Building," Energies, MDPI, vol. 16(13), pages 1-24, June.
    7. Saeed Salah & Husain R. Alsamamra & Jawad H. Shoqeir, 2022. "Exploring Wind Speed for Energy Considerations in Eastern Jerusalem-Palestine Using Machine-Learning Algorithms," Energies, MDPI, vol. 15(7), pages 1-16, April.
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