IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v14y2021i8p2180-d535752.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/14/8/2180/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/14/8/2180/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    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).
    2. Chantrelle, Fanny Pernodet & Lahmidi, Hicham & Keilholz, Werner & Mankibi, Mohamed El & Michel, Pierre, 2011. "Development of a multicriteria tool for optimizing the renovation of buildings," Applied Energy, Elsevier, vol. 88(4), pages 1386-1394, April.
    3. Karmellos, M. & Kiprakis, A. & Mavrotas, G., 2015. "A multi-objective approach for optimal prioritization of energy efficiency measures in buildings: Model, software and case studies," Applied Energy, Elsevier, vol. 139(C), pages 131-150.
    4. Mohammadi, Zahra & Hoes, Pieter Jan & Hensen, Jan L.M., 2020. "Simulation-based design optimization of houses with low grid dependency," Renewable Energy, Elsevier, vol. 157(C), pages 1185-1202.
    5. Delgarm, N. & Sajadi, B. & Kowsary, F. & Delgarm, S., 2016. "Multi-objective optimization of the building energy performance: A simulation-based approach by means of particle swarm optimization (PSO)," Applied Energy, Elsevier, vol. 170(C), pages 293-303.
    6. Schwartz, Yair & Raslan, Rokia & Mumovic, Dejan, 2016. "Implementing multi objective genetic algorithm for life cycle carbon footprint and life cycle cost minimisation: A building refurbishment case study," Energy, Elsevier, vol. 97(C), pages 58-68.
    7. Foucquier, Aurélie & Robert, Sylvain & Suard, Frédéric & Stéphan, Louis & Jay, Arnaud, 2013. "State of the art in building modelling and energy performances prediction: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 23(C), pages 272-288.
    8. Taveres-Cachat, Ellika & Lobaccaro, Gabriele & Goia, Francesco & Chaudhary, Gaurav, 2019. "A methodology to improve the performance of PV integrated shading devices using multi-objective optimization," Applied Energy, Elsevier, vol. 247(C), pages 731-744.
    9. Wu, Raphael & Mavromatidis, Georgios & Orehounig, Kristina & Carmeliet, Jan, 2017. "Multiobjective optimisation of energy systems and building envelope retrofit in a residential community," Applied Energy, Elsevier, vol. 190(C), pages 634-649.
    10. Hong, Taehoon & Kim, Jimin & Lee, Minhyun, 2019. "A multi-objective optimization model for determining the building design and occupant behaviors based on energy, economic, and environmental performance," Energy, Elsevier, vol. 174(C), pages 823-834.
    11. Harkouss, Fatima & Fardoun, Farouk & Biwole, Pascal Henry, 2018. "Passive design optimization of low energy buildings in different climates," Energy, Elsevier, vol. 165(PA), pages 591-613.
    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. 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).

    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. 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).
    2. Kangji Li & Lei Pan & Wenping Xue & Hui Jiang & Hanping Mao, 2017. "Multi-Objective Optimization for Energy Performance Improvement of Residential Buildings: A Comparative Study," Energies, MDPI, vol. 10(2), pages 1-23, February.
    3. Ascione, Fabrizio & Bianco, Nicola & Mauro, Gerardo Maria & Vanoli, Giuseppe Peter, 2019. "A new comprehensive framework for the multi-objective optimization of building energy design: Harlequin," Applied Energy, Elsevier, vol. 241(C), pages 331-361.
    4. Ascione, Fabrizio & Bianco, Nicola & De Stasio, Claudio & Mauro, Gerardo Maria & Vanoli, Giuseppe Peter, 2016. "Multi-stage and multi-objective optimization for energy retrofitting a developed hospital reference building: A new approach to assess cost-optimality," Applied Energy, Elsevier, vol. 174(C), pages 37-68.
    5. Shaoxiong Li & Le Liu & Changhai Peng, 2020. "A Review of Performance-Oriented Architectural Design and Optimization in the Context of Sustainability: Dividends and Challenges," Sustainability, MDPI, vol. 12(4), pages 1-36, February.
    6. Ceballos-Fuentealba, Irlanda & Álvarez-Miranda, Eduardo & Torres-Fuchslocher, Carlos & del Campo-Hitschfeld, María Luisa & Díaz-Guerrero, John, 2019. "A simulation and optimisation methodology for choosing energy efficiency measures in non-residential buildings," Applied Energy, Elsevier, vol. 256(C).
    7. Wu, Raphael & Mavromatidis, Georgios & Orehounig, Kristina & Carmeliet, Jan, 2017. "Multiobjective optimisation of energy systems and building envelope retrofit in a residential community," Applied Energy, Elsevier, vol. 190(C), pages 634-649.
    8. Ali Sadollah & Mohammad Nasir & Zong Woo Geem, 2020. "Sustainability and Optimization: From Conceptual Fundamentals to Applications," Sustainability, MDPI, vol. 12(5), pages 1-34, March.
    9. Diana Manjarres & Lara Mabe & Xabat Oregi & Itziar Landa-Torres, 2019. "Two-Stage Multi-Objective Meta-Heuristics for Environmental and Cost-Optimal Energy Refurbishment at District Level," Sustainability, MDPI, vol. 11(5), pages 1-24, March.
    10. Schito, Eva & Conti, Paolo & Testi, Daniele, 2018. "Multi-objective optimization of microclimate in museums for concurrent reduction of energy needs, visitors’ discomfort and artwork preservation risks," Applied Energy, Elsevier, vol. 224(C), pages 147-159.
    11. Wang, Ran & Lu, Shilei & Feng, Wei, 2020. "A three-stage optimization methodology for envelope design of passive house considering energy demand, thermal comfort and cost," Energy, Elsevier, vol. 192(C).
    12. García Kerdan, Iván & Raslan, Rokia & Ruyssevelt, Paul & Morillón Gálvez, David, 2017. "A comparison of an energy/economic-based against an exergoeconomic-based multi-objective optimisation for low carbon building energy design," Energy, Elsevier, vol. 128(C), pages 244-263.
    13. Lee, Junghun & Kim, Jeonggook & Song, Doosam & Kim, Jonghun & Jang, Cheolyong, 2017. "Impact of external insulation and internal thermal density upon energy consumption of buildings in a temperate climate with four distinct seasons," Renewable and Sustainable Energy Reviews, Elsevier, vol. 75(C), pages 1081-1088.
    14. O'Grady, Małgorzata & Lechowska, Agnieszka A. & Harte, Annette M., 2017. "Quantification of heat losses through building envelope thermal bridges influenced by wind velocity using the outdoor infrared thermography technique," Applied Energy, Elsevier, vol. 208(C), pages 1038-1052.
    15. Prada, A. & Gasparella, A. & Baggio, P., 2018. "On the performance of meta-models in building design optimization," Applied Energy, Elsevier, vol. 225(C), pages 814-826.
    16. Seyedeh Farzaneh Mousavi Motlagh & Ali Sohani & Mohammad Djavad Saghafi & Hoseyn Sayyaadi & Benedetto Nastasi, 2021. "The Road to Developing Economically Feasible Plans for Green, Comfortable and Energy Efficient Buildings," Energies, MDPI, vol. 14(3), pages 1-30, January.
    17. Cristina Baglivo & Delia D’Agostino & Paolo Maria Congedo, 2018. "Design of a Ventilation System Coupled with a Horizontal Air-Ground Heat Exchanger (HAGHE) for a Residential Building in a Warm Climate," Energies, MDPI, vol. 11(8), pages 1-27, August.
    18. Delgarm, N. & Sajadi, B. & Kowsary, F. & Delgarm, S., 2016. "Multi-objective optimization of the building energy performance: A simulation-based approach by means of particle swarm optimization (PSO)," Applied Energy, Elsevier, vol. 170(C), pages 293-303.
    19. Li, Hong Xian & Li, Yan & Jiang, Boya & Zhang, Limao & Wu, Xianguo & Lin, Jingyi, 2020. "Energy performance optimisation of building envelope retrofit through integrated orthogonal arrays with data envelopment analysis," Renewable Energy, Elsevier, vol. 149(C), pages 1414-1423.
    20. Zahra Fallahi & Gregor P. Henze, 2019. "Interactive Buildings: A Review," Sustainability, MDPI, vol. 11(14), pages 1-26, July.

    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:14:y:2021:i:8:p:2180-:d:535752. 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.