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Building Retrofitting through Coupling of Building Energy Simulation-Optimization Tool with CFD and Daylight Programs

Author

Listed:
  • Mehrdad Rabani

    (Department of Civil Engineering and Energy Technology, Oslo Metropolitan University, 0130 Oslo, Norway
    Department of Energy and Process Engineering, Norwegian University of Science and Technology, 7491 Trondheim, Norway)

  • Habtamu Bayera Madessa

    (Department of Civil Engineering and Energy Technology, Oslo Metropolitan University, 0130 Oslo, Norway)

  • Natasa Nord

    (Department of Energy and Process Engineering, Norwegian University of Science and Technology, 7491 Trondheim, Norway)

Abstract

Simultaneous satisfaction of both thermal and visual comfort in buildings may be a challenging task. Therefore, this paper suggests a comprehensive framework for the building energy optimization process integrating computational fluid dynamics (CFD) daylight simulations. A building energy simulation tool, IDA Indoor Climate and Energy (IDA-ICE), was coupled with three open-source tools including GenOpt, OpenFOAM, and Radiance. In the optimization phase, several design variables i.e., building envelope properties, fenestration parameters, and Heating, Ventilation and Air-Conditioning (HVAC) system set points, were selected to minimize the total building energy use and simultaneously improve thermal and visual comfort. Two different scenarios were investigated for retrofitting of a generic office building located in Oslo, Norway. In the first scenario a constant air volume (CAV) ventilation system with a local radiator in each zone was used, while an all-air system equipped with a demand control ventilation (DCV) was applied in the second scenario. Findings showed that, compared to the reference design, significant reduction of total building energy use, around 77% and 79% in the first and second scenarios, was achieved respectively, and thermal and visual comfort conditions were also improved considerably. However, the overall thermal and visual comfort satisfactions were higher when all-air system was applied.

Suggested Citation

  • Mehrdad Rabani & Habtamu Bayera Madessa & Natasa Nord, 2021. "Building Retrofitting through Coupling of Building Energy Simulation-Optimization Tool with CFD and Daylight Programs," Energies, MDPI, vol. 14(8), pages 1-23, April.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:8:p:2180-:d:535752
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    References listed on IDEAS

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    1. Rabani, Mehrdad & Bayera Madessa, Habtamu & Mohseni, Omid & Nord, Natasa, 2020. "Minimizing delivered energy and life cycle cost using Graphical script: An office building retrofitting case," Applied Energy, Elsevier, vol. 268(C).
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    Cited by:

    1. Konstantinos Sofias & Zoe Kanetaki & Constantinos Stergiou & Sébastien Jacques, 2023. "Combining CAD Modeling and Simulation of Energy Performance Data for the Retrofit of Public Buildings," Sustainability, MDPI, vol. 15(3), pages 1-21, January.
    2. Konrad Nering & Krzysztof Nering, 2021. "Validation of Modified Algebraic Model during Transitional Flow in HVAC Duct," Energies, MDPI, vol. 14(13), pages 1-20, July.
    3. Tatsuhiro Yamamoto & Akihito Ozaki & Myonghyang Lee, 2021. "Optimal Air Conditioner Placement Using a Simple Thermal Environment Analysis Method for Continuous Large Spaces with Predominant Advection," Energies, MDPI, vol. 14(15), pages 1-24, July.
    4. Jiao Xue & Yige Fan & Zhanxun Dong & Xiao Hu & Jiatong Yue, 2022. "Improving Visual Comfort and Health through the Design of a Local Shading Device," IJERPH, MDPI, vol. 19(7), pages 1-20, April.
    5. George M. Stavrakakis & Dimitris Al. Katsaprakakis & Markos Damasiotis, 2021. "Basic Principles, Most Common Computational Tools, and Capabilities for Building Energy and Urban Microclimate Simulations," Energies, MDPI, vol. 14(20), pages 1-41, October.
    6. Seyedmohammadreza Heibati & Wahid Maref & Hamed H. Saber, 2021. "Assessing the Energy, Indoor Air Quality, and Moisture Performance for a Three-Story Building Using an Integrated Model, Part Two: Integrating the Indoor Air Quality, Moisture, and Thermal Comfort," Energies, MDPI, vol. 14(16), pages 1-40, August.
    7. Pinto, Maria Cristina & Crespi, Giulia & Dell'Anna, Federico & Becchio, Cristina, 2023. "Combining energy dynamic simulation and multi-criteria analysis for supporting investment decisions on smart shading devices in office buildings," Applied Energy, Elsevier, vol. 332(C).

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