IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v16y2023i24p7958-d1296094.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/16/24/7958/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/16/24/7958/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    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. 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.
    3. 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.
    4. 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.
    5. 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.
    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.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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.
    2. Piotr Michalak, 2022. "Thermal—Airflow Coupling in Hourly Energy Simulation of a Building with Natural Stack Ventilation," Energies, MDPI, vol. 15(11), pages 1-18, June.
    3. Khencha Khadidja & Biara Ratiba Wided & Belmili Hocine, 2020. "Techno-economic study of BIPV in typical Sahara region in Algeria," Journal of Economic Development, Environment and People, Alliance of Central-Eastern European Universities, vol. 9(1), pages 27-57, September.
    4. Hu, Jianming & Wang, Jianzhou & Zeng, Guowei, 2013. "A hybrid forecasting approach applied to wind speed time series," Renewable Energy, Elsevier, vol. 60(C), pages 185-194.
    5. Sabina Kordana-Obuch & Michał Wojtoń & Mariusz Starzec & Beata Piotrowska, 2023. "Opportunities and Challenges for Research on Heat Recovery from Wastewater: Bibliometric and Strategic Analyses," Energies, MDPI, vol. 16(17), pages 1-36, September.
    6. Santamaría-Bonfil, G. & Reyes-Ballesteros, A. & Gershenson, C., 2016. "Wind speed forecasting for wind farms: A method based on support vector regression," Renewable Energy, Elsevier, vol. 85(C), pages 790-809.
    7. Niu, Tong & Wang, Jianzhou & Zhang, Kequan & Du, Pei, 2018. "Multi-step-ahead wind speed forecasting based on optimal feature selection and a modified bat algorithm with the cognition strategy," Renewable Energy, Elsevier, vol. 118(C), pages 213-229.
    8. Mehrpooya, Mehdi & Ansarinasab, Hojat & Mousavi, Seyed Ali, 2021. "Life cycle assessment and exergoeconomic analysis of the multi-generation system based on fuel cell for methanol, power, and heat production," Renewable Energy, Elsevier, vol. 172(C), pages 1314-1332.
    9. Wang, Jianzhou & Qin, Shanshan & Zhou, Qingping & Jiang, Haiyan, 2015. "Medium-term wind speeds forecasting utilizing hybrid models for three different sites in Xinjiang, China," Renewable Energy, Elsevier, vol. 76(C), pages 91-101.
    10. Moldovan, Camelia Liliana & Păltănea, Radu & Visa, Ion, 2020. "Improvement of clear sky models for direct solar irradiance considering turbidity factor variable during the day," Renewable Energy, Elsevier, vol. 161(C), pages 559-569.
    11. Marta Laska & Katarzyna Reclik, 2024. "Analysis of Internal Conditions and Energy Consumption during Winter in an Apartment Located in a Tenement Building in Poland," Sustainability, MDPI, vol. 16(10), pages 1-21, May.
    12. Andrea Frattolillo & Laura Canale & Giorgio Ficco & Costantino C. Mastino & Marco Dell’Isola, 2020. "Potential for Building Façade-Integrated Solar Thermal Collectors in a Highly Urbanized Context," Energies, MDPI, vol. 13(21), pages 1-18, November.
    13. Hassan, Atazaz & Quanfang, Chen & Abbas, Sajid & Lu, Wu & Youming, Luo, 2021. "An experimental investigation on thermal and optical analysis of cylindrical and conical cavity copper tube receivers design for solar dish concentrator," Renewable Energy, Elsevier, vol. 179(C), pages 1849-1864.
    14. Danxiang Wei & Jianzhou Wang & Kailai Ni & Guangyu Tang, 2019. "Research and Application of a Novel Hybrid Model Based on a Deep Neural Network Combined with Fuzzy Time Series for Energy Forecasting," Energies, MDPI, vol. 12(18), pages 1-38, September.
    15. Zhao, Jing & Guo, Zhenhai & Guo, Yanling & Lin, Wantao & Zhu, Wenjin, 2021. "A self-organizing forecast of day-ahead wind speed: Selective ensemble strategy based on numerical weather predictions," Energy, Elsevier, vol. 218(C).
    16. Hassan Gholami & Harald Nils Røstvik & Koen Steemers, 2021. "The Contribution of Building-Integrated Photovoltaics (BIPV) to the Concept of Nearly Zero-Energy Cities in Europe: Potential and Challenges Ahead," Energies, MDPI, vol. 14(19), pages 1-22, September.
    17. Wang, Chuyao & Ji, Jie & Zhang, Chengyan & Ke, Wei & Tang, Yayun & Tian, Xinyi, 2022. "Experimental and numerical investigation of a multi-functional photovoltaic/thermal wall: A practical application in the civil building," Energy, Elsevier, vol. 241(C).
    18. Wu, Jie & Li, Na & Zhao, Yan & Wang, Jujie, 2022. "Usage of correlation analysis and hypothesis test in optimizing the gated recurrent unit network for wind speed forecasting," Energy, Elsevier, vol. 242(C).
    19. Manoj Verma & Harish Kumar Ghritlahre, 2023. "Forecasting of Wind Speed by Using Three Different Techniques of Prediction Models," Annals of Data Science, Springer, vol. 10(3), pages 679-711, June.
    20. Teng, Sin Yong & Máša, Vítězslav & Touš, Michal & Vondra, Marek & Lam, Hon Loong & Stehlík, Petr, 2022. "Waste-to-energy forecasting and real-time optimization: An anomaly-aware approach," Renewable Energy, Elsevier, vol. 181(C), pages 142-155.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:16:y:2023:i:24:p:7958-:d:1296094. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.