IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v13y2021i15p8646-d607406.html
   My bibliography  Save this article

Influence of Thermal Enclosures on Energy Saving Simulations of Residential Building Typologies in European Climatic Zones

Author

Listed:
  • José Miguel Márquez-Martinón

    (Departamento de Técnicas y Proyectos en Ingeniería y Arquitectura, Universidad de La Laguna, Avenida Ángel Guimerá Jorge, s/n., 38200 La Laguna, Spain)

  • Norena Martín-Dorta

    (Departamento de Técnicas y Proyectos en Ingeniería y Arquitectura, Universidad de La Laguna, Avenida Ángel Guimerá Jorge, s/n., 38200 La Laguna, Spain)

  • Eduardo González-Díaz

    (Departamento de Técnicas y Proyectos en Ingeniería y Arquitectura, Universidad de La Laguna, Avenida Ángel Guimerá Jorge, s/n., 38200 La Laguna, Spain)

  • Benjamín González-Díaz

    (Departamento de Ingeniería Industrial, Universidad de La Laguna, Camino San Francisco de Paula, s/n., 38200 La Laguna, Spain)

Abstract

Nowadays, the computational simulation of the energy consumption in buildings is a key issue to determine the most proficient configuration between the construction solutions and the necessary equipment, without compromising comfort and accomplishing the legal requirements for each country. The feasible and most profitable solutions can lead to minimizing CO 2 emissions and environmental impact. In this work, the internal enclosures influencing the evaluation of energy consumption by energy simulation have been analysed in order to obtain an accurate solution when all the information regarding the internal partitions is not available. The main aim of the present research was to evaluate the role of internal distribution in the simulations of the total building energy consumption. Differences between the results of the energy simulations of buildings that are calculated considering their internal distribution, and those in which only the exterior geometry that makes up the perimeter of the envelope are being described. In this way, it is intended to establish a correction factor based on the building typology and the European climate zone that allows simulation tools to describe the energy reality of a building without knowing its internal distribution.

Suggested Citation

  • José Miguel Márquez-Martinón & Norena Martín-Dorta & Eduardo González-Díaz & Benjamín González-Díaz, 2021. "Influence of Thermal Enclosures on Energy Saving Simulations of Residential Building Typologies in European Climatic Zones," Sustainability, MDPI, vol. 13(15), pages 1-19, August.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:15:p:8646-:d:607406
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/13/15/8646/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/13/15/8646/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Menezes, Anna Carolina & Cripps, Andrew & Bouchlaghem, Dino & Buswell, Richard, 2012. "Predicted vs. actual energy performance of non-domestic buildings: Using post-occupancy evaluation data to reduce the performance gap," Applied Energy, Elsevier, vol. 97(C), pages 355-364.
    2. Kamel, Ehsan & Memari, Ali M., 2018. "Automated Building Energy Modeling and Assessment Tool (ABEMAT)," Energy, Elsevier, vol. 147(C), pages 15-24.
    3. WoonSeong Jeong & JeongWook Son, 2016. "An Algorithm to Translate Building Topology in Building Information Modeling into Object-Oriented Physical Modeling-Based Building Energy Modeling," Energies, MDPI, vol. 9(1), pages 1-23, January.
    4. Naveed Ahmad & Christian Ghiaus & Moomal Qureshi, 2020. "Error Analysis of QUB Method in Non-Ideal Conditions during the Experiment," Energies, MDPI, vol. 13(13), pages 1-17, July.
    5. WoonSeong Jeong & Kee Han Kim, 2016. "A Performance Evaluation of the BIM-Based Object-Oriented Physical Modeling Technique for Building Thermal Simulations: A Comparative Case Study," Sustainability, MDPI, vol. 8(7), pages 1-27, July.
    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. Gao, Hao & Koch, Christian & Wu, Yupeng, 2019. "Building information modelling based building energy modelling: A review," Applied Energy, Elsevier, vol. 238(C), pages 320-343.
    2. Habtamu Tkubet Ebuy & Hind Bril El Haouzi & Riad Benelmir & Remi Pannequin, 2023. "Occupant Behavior Impact on Building Sustainability Performance: A Literature Review," Sustainability, MDPI, vol. 15(3), pages 1-23, January.
    3. Anti Hamburg & Targo Kalamees, 2018. "The Influence of Energy Renovation on the Change of Indoor Temperature and Energy Use," Energies, MDPI, vol. 11(11), pages 1-15, November.
    4. Jakob Carlander & Bahram Moshfegh & Jan Akander & Fredrik Karlsson, 2020. "Effects on Energy Demand in an Office Building Considering Location, Orientation, Façade Design and Internal Heat Gains—A Parametric Study," Energies, MDPI, vol. 13(23), pages 1-22, November.
    5. Alencastro, João & Fuertes, Alba & de Wilde, Pieter, 2018. "The relationship between quality defects and the thermal performance of buildings," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 883-894.
    6. Prasanna, Ashreeta & Dorer, Viktor & Vetterli, Nadège, 2017. "Optimisation of a district energy system with a low temperature network," Energy, Elsevier, vol. 137(C), pages 632-648.
    7. 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.
    8. Zhong, Shengyuan & Zhao, Jun & Li, Wenjia & Li, Hao & Deng, Shuai & Li, Yang & Hussain, Sajjad & Wang, Xiaoyuan & Zhu, Jiebei, 2021. "Quantitative analysis of information interaction in building energy systems based on mutual information," Energy, Elsevier, vol. 214(C).
    9. Eugene Mohareb & Arman Hashemi & Mehdi Shahrestani & Minna Sunikka-Blank, 2017. "Retrofit Planning for the Performance Gap: Results of a Workshop on Addressing Energy, Health and Comfort Needs in a Protected Building," Energies, MDPI, vol. 10(8), pages 1-17, August.
    10. Pierryves Padey & Kyriaki Goulouti & Guy Wagner & Blaise Périsset & Sébastien Lasvaux, 2021. "Understanding the Reasons behind the Energy Performance Gap of an Energy-Efficient Building, through a Probabilistic Approach and On-Site Measurements," Energies, MDPI, vol. 14(19), pages 1-15, September.
    11. Gupta, Rajat & Kotopouleas, Alkis, 2018. "Magnitude and extent of building fabric thermal performance gap in UK low energy housing," Applied Energy, Elsevier, vol. 222(C), pages 673-686.
    12. Wang, Lan & Lee, Eric W.M. & Hussian, Syed Asad & Yuen, Anthony Chun Yin & Feng, Wei, 2021. "Quantitative impact analysis of driving factors on annual residential building energy end-use combining machine learning and stochastic methods," Applied Energy, Elsevier, vol. 299(C).
    13. De Boeck, L. & Verbeke, S. & Audenaert, A. & De Mesmaeker, L., 2015. "Improving the energy performance of residential buildings: A literature review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 52(C), pages 960-975.
    14. Abdulazeez Rotimi & Ali Bahadori-Jahromi & Anastasia Mylona & Paulina Godfrey & Darren Cook, 2017. "Estimation and Validation of Energy Consumption in UK Existing Hotel Building Using Dynamic Simulation Software," Sustainability, MDPI, vol. 9(8), pages 1-18, August.
    15. Li, Xinyi & Yao, Runming & Li, Qin & Ding, Yong & Li, Baizhan, 2018. "An object-oriented energy benchmark for the evaluation of the office building stock," Utilities Policy, Elsevier, vol. 51(C), pages 1-11.
    16. Qadeer Ali & Muhammad Jamaluddin Thaheem & Fahim Ullah & Samad M. E. Sepasgozar, 2020. "The Performance Gap in Energy-Efficient Office Buildings: How the Occupants Can Help?," Energies, MDPI, vol. 13(6), pages 1-27, March.
    17. Azar, Elie & Nikolopoulou, Christina & Papadopoulos, Sokratis, 2016. "Integrating and optimizing metrics of sustainable building performance using human-focused agent-based modeling," Applied Energy, Elsevier, vol. 183(C), pages 926-937.
    18. Ji, Changyoon & Hong, Taehoon & Kim, Hakpyeong, 2022. "Statistical analysis of greenhouse gas emissions of South Korean residential buildings," Renewable and Sustainable Energy Reviews, Elsevier, vol. 156(C).
    19. Zulay Giménez & Claudio Mourgues & Luis F. Alarcón & Harrison Mesa & Eugenio Pellicer, 2020. "Value Analysis Model to Support the Building Design Process," Sustainability, MDPI, vol. 12(10), pages 1-24, May.
    20. Naylor, Sophie & Gillott, Mark & Lau, Tom, 2018. "A review of occupant-centric building control strategies to reduce building energy use," Renewable and Sustainable Energy Reviews, Elsevier, vol. 96(C), pages 1-10.

    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:jsusta:v:13:y:2021:i:15:p:8646-:d:607406. 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.