IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v12y2019i17p3360-d262739.html
   My bibliography  Save this article

Energy Modelling and Calibration of Building Simulations: A Case Study of a Domestic Building with Natural Ventilation

Author

Listed:
  • Carolina Aparicio-Fernández

    (Departamento de Construciones Arquitectonicas, Universitat Politècnica de València, Camino de Vera s/n., 46022 Valencia, Spain
    These authors contributed equally to this work.)

  • José-Luis Vivancos

    (GIDDP, Departamento de Proyectos de Ingeniería, Universitat Politècnica de València, Camino de Vera s/n., 46022 Valencia, Spain
    These authors contributed equally to this work.)

  • Paula Cosar-Jorda

    (School of Architecture, Building and Civil Engineering, Loughborough University, Loughborough LE11 3TU, UK)

  • Richard A. Buswell

    (School of Architecture, Building and Civil Engineering, Loughborough University, Loughborough LE11 3TU, UK)

Abstract

In this paper, the building energy performance modelling tools TRNSYS (TRaNsient SYstem Simulation program) and TRNFlow (TRaNsient Flow) have been used to obtain the energy demand of a domestic building that includes the air infiltration rate and the effect of natural ventilation by using window operation data. An initial model has been fitted to monitoring data from the case study, building over a period when there were no heat gains in the building in order to obtain the building infiltration air change rate. After this calibration, a constant air-change rate model was established alongside two further models developed in the calibration process. Air change rate has been explored in order to determine air infiltrations caused by natural ventilation due to windows being opened. These results were compared to estimates gained through a previously published method and were found to be in good agreement. The main conclusion from the work was that the modelling ventilation rate in naturally ventilated residential buildings using TRNSYS and TRNSFlow can improve the simulation-based energy assessment.

Suggested Citation

  • Carolina Aparicio-Fernández & José-Luis Vivancos & Paula Cosar-Jorda & Richard A. Buswell, 2019. "Energy Modelling and Calibration of Building Simulations: A Case Study of a Domestic Building with Natural Ventilation," Energies, MDPI, vol. 12(17), pages 1-13, August.
  • Handle: RePEc:gam:jeners:v:12:y:2019:i:17:p:3360-:d:262739
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/12/17/3360/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/12/17/3360/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ana Ogando & Natalia Cid & Marta Fernández, 2017. "Energy Modelling and Automated Calibrations of Ancient Building Simulations: A Case Study of a School in the Northwest of Spain," Energies, MDPI, vol. 10(6), pages 1-17, June.
    2. Lamberto Tronchin & Kristian Fabbri & Chiara Bertolli, 2018. "Controlled Mechanical Ventilation in Buildings: A Comparison between Energy Use and Primary Energy among Twenty Different Devices," Energies, MDPI, vol. 11(8), pages 1-19, August.
    3. Krzysztof Grygierek & Joanna Ferdyn-Grygierek, 2018. "Multi-Objective Optimization of the Envelope of Building with Natural Ventilation," Energies, MDPI, vol. 11(6), pages 1-17, May.
    4. Hong, Tianzhen & Piette, Mary Ann & Chen, Yixing & Lee, Sang Hoon & Taylor-Lange, Sarah C. & Zhang, Rongpeng & Sun, Kaiyu & Price, Phillip, 2015. "Commercial Building Energy Saver: An energy retrofit analysis toolkit," Applied Energy, Elsevier, vol. 159(C), pages 298-309.
    5. Germán Ramos Ruiz & Carlos Fernández Bandera, 2017. "Validation of Calibrated Energy Models: Common Errors," Energies, MDPI, vol. 10(10), pages 1-19, October.
    6. Samuel Domínguez-Amarillo & Jesica Fernández-Agüera & Miguel Ángel Campano & Ignacio Acosta, 2019. "Effect of Airtightness on Thermal Loads in Legacy Low-Income Housing," Energies, MDPI, vol. 12(9), pages 1-14, May.
    7. Jesús Feijó-Muñoz & Irene Poza-Casado & Roberto Alonso González-Lezcano & Cristina Pardal & Víctor Echarri & Rafael Assiego De Larriva & Jesica Fernández-Agüera & María Jesús Dios-Viéitez & Víctor Jos, 2018. "Methodology for the Study of the Envelope Airtightness of Residential Buildings in Spain: A Case Study," Energies, MDPI, vol. 11(4), pages 1-20, March.
    8. Mahabir Bhandari & Diana Hun & Som Shrestha & Simon Pallin & Melissa Lapsa, 2018. "A Simplified Methodology to Estimate Energy Savings in Commercial Buildings from Improvements in Airtightness," Energies, MDPI, vol. 11(12), pages 1-16, November.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Binju P Raj & Chandan Swaroop Meena & Nehul Agarwal & Lohit Saini & Shabir Hussain Khahro & Umashankar Subramaniam & Aritra Ghosh, 2021. "A Review on Numerical Approach to Achieve Building Energy Efficiency for Energy, Economy and Environment (3E) Benefit," Energies, MDPI, vol. 14(15), pages 1-26, July.
    2. Víctor Pérez-Andreu & Carolina Aparicio-Fernández & José-Luis Vivancos & Javier Cárcel-Carrasco, 2021. "Experimental Data and Simulations of Performance and Thermal Comfort in a Typical Mediterranean House," Energies, MDPI, vol. 14(11), pages 1-14, June.
    3. Joanna Ferdyn-Grygierek & Andrzej Baranowski & Monika Blaszczok & Jan Kaczmarczyk, 2019. "Thermal Diagnostics of Natural Ventilation in Buildings: An Integrated Approach," Energies, MDPI, vol. 12(23), pages 1-22, November.
    4. Olivier Dartevelle & Sergio Altomonte & Gabrielle Masy & Erwin Mlecnik & Geoffrey van Moeseke, 2022. "Indoor Summer Thermal Comfort in a Changing Climate: The Case of a Nearly Zero Energy House in Wallonia (Belgium)," Energies, MDPI, vol. 15(7), pages 1-13, March.
    5. Sanjin Gumbarević & Ivana Burcar Dunović & Bojan Milovanović & Mergim Gaši, 2020. "Method for Building Information Modeling Supported Project Control of Nearly Zero-Energy Building Delivery," Energies, MDPI, vol. 13(20), pages 1-21, October.

    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. Valdas Paukštys & Gintaris Cinelis & Jūratė Mockienė & Mindaugas Daukšys, 2021. "Airtightness and Heat Energy Loss of Mid-Size Terraced Houses Built of Different Construction Materials," Energies, MDPI, vol. 14(19), pages 1-23, October.
    2. Artur Nowoświat & Iwona Pokorska-Silva & Mateusz Konewecki, 2021. "Tightness of Single-Family Buildings Made in Prefabricated Wood Frame Technology," Energies, MDPI, vol. 14(15), pages 1-14, July.
    3. Rachael Sherman & Hariharan Naganathan & Kristen Parrish, 2021. "Energy Savings Results from Small Commercial Building Retrofits in the US," Energies, MDPI, vol. 14(19), pages 1-16, September.
    4. Žižak, Tej & Domjan, Suzana & Medved, Sašo & Arkar, Ciril, 2022. "Efficiency and sustainability assessment of evaporative cooling of photovoltaics," Energy, Elsevier, vol. 254(PA).
    5. Martín Pensado-Mariño & Lara Febrero-Garrido & Pablo Eguía-Oller & Enrique Granada-Álvarez, 2021. "Feasibility of Different Weather Data Sources Applied to Building Indoor Temperature Estimation Using LSTM Neural Networks," Sustainability, MDPI, vol. 13(24), pages 1-15, December.
    6. Abdelhakim Mesloub & Aritra Ghosh & Mabrouk Touahmia & Ghazy Abdullah Albaqawy & Emad Noaime & Badr M. Alsolami, 2020. "Performance Analysis of Photovoltaic Integrated Shading Devices (PVSDs) and Semi-Transparent Photovoltaic (STPV) Devices Retrofitted to a Prototype Office Building in a Hot Desert Climate," Sustainability, MDPI, vol. 12(23), pages 1-17, December.
    7. Kittisak Lohwanitchai & Daranee Jareemit, 2021. "Modeling Energy Efficiency Performance and Cost-Benefit Analysis Achieving Net-Zero Energy Building Design: Case Studies of Three Representative Offices in Thailand," Sustainability, MDPI, vol. 13(9), pages 1-24, May.
    8. Lorenzo Gragnaniello & Marcello Iasiello & Gerardo Maria Mauro, 2022. "Multi-Objective Optimization of a Heat Sink for the Thermal Management of a Peltier-Cell-Based Biomedical Refrigerator," Energies, MDPI, vol. 15(19), pages 1-12, October.
    9. Evelina Di Corso & Tania Cerquitelli & Daniele Apiletti, 2018. "METATECH: METeorological Data Analysis for Thermal Energy CHaracterization by Means of Self-Learning Transparent Models," Energies, MDPI, vol. 11(6), pages 1-24, May.
    10. Gigih Rahmandhani Setyantho & Hansaem Park & Seongju Chang, 2021. "Multi-Criteria Performance Assessment for Semi-Transparent Photovoltaic Windows in Different Climate Contexts," Sustainability, MDPI, vol. 13(4), pages 1-21, February.
    11. Piotr Ciuman & Jan Kaczmarczyk, 2021. "Numerical Analysis of the Energy Consumption of Ventilation Processes in the School Swimming Pool," Energies, MDPI, vol. 14(4), pages 1-18, February.
    12. Katarzyna Gładyszewska-Fiedoruk & Vasyl Zhelykh & Andrii Pushchinskyi, 2019. "RETRACTED: Simulation and Analysis of Various Ventilation Systems Given in an Example in the Same School of Indoor Air Quality," Energies, MDPI, vol. 12(15), pages 1, July.
    13. 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.
    14. Sun, Kaiyu & Hong, Tianzhen & Taylor-Lange, Sarah C. & Piette, Mary Ann, 2016. "A pattern-based automated approach to building energy model calibration," Applied Energy, Elsevier, vol. 165(C), pages 214-224.
    15. Suzana Domjan & Sašo Medved & Boštjan Černe & Ciril Arkar, 2019. "Fast Modelling of nZEB Metrics of Office Buildings Built with Advanced Glass and BIPV Facade Structures," Energies, MDPI, vol. 12(16), pages 1-18, August.
    16. Amin, Amin & Mourshed, Monjur, 2024. "Community stochastic domestic electricity forecasting," Applied Energy, Elsevier, vol. 355(C).
    17. Ana Ogando-Martínez & Javier López-Gómez & Lara Febrero-Garrido, 2018. "Maintenance Factor Identification in Outdoor Lighting Installations Using Simulation and Optimization Techniques," Energies, MDPI, vol. 11(8), pages 1-13, August.
    18. Robinson, Caleb & Dilkina, Bistra & Hubbs, Jeffrey & Zhang, Wenwen & Guhathakurta, Subhrajit & Brown, Marilyn A. & Pendyala, Ram M., 2017. "Machine learning approaches for estimating commercial building energy consumption," Applied Energy, Elsevier, vol. 208(C), pages 889-904.
    19. Shamsi, Mohammad Haris & Ali, Usman & Mangina, Eleni & O’Donnell, James, 2021. "Feature assessment frameworks to evaluate reduced-order grey-box building energy models," Applied Energy, Elsevier, vol. 298(C).
    20. 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.

    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:12:y:2019:i:17:p:3360-:d:262739. 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.