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Passive design optimization of low energy buildings in different climates

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  • Harkouss, Fatima
  • Fardoun, Farouk
  • Biwole, Pascal Henry

Abstract

Worldwide, the residential buildings are consuming a considerable amount of energy. The high potential of buildings towards energy efficiency has drawn special attention to the passive design parameters. A comprehensive study on optimal passive design for residential buildings is presented in this paper. Twenty-five different climates are simulated with the aim to produce best practices to reduce building energy demands (for cooling and heating) in addition to the life-cycle cost (LCC). The occupants' adaptive thermal comfort is also improved by implementing the appropriate passive cooling strategies such as blinds and natural ventilation. In this respect, the implemented methodology is composed of four phases: building energy simulation, optimization, Multi-criteria Decision Making (MCDM), sensitivity study, and finally an adaptive comfort analysis. An optimal passive solution of the studied building indicates the potential to save up to 54%, 87% and 52% of the cooling demands (Qcool), heating demands (Qheat) and LCC respectively with respect to the initial configuration. The obtained optimal passive parameters are validated with the National Renewable Energy Laboratory NREL benchmark for low energy building's envelope. Additionally, the integrated passive cooling strategies have demonstrated its competency since it leads to a significant overheating decrease.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:energy:v:165:y:2018:i:pa:p:591-613
    DOI: 10.1016/j.energy.2018.09.019
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    1. 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.
    2. Machairas, Vasileios & Tsangrassoulis, Aris & Axarli, Kleo, 2014. "Algorithms for optimization of building design: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 31(C), pages 101-112.
    3. Zhang, Yu & Zhang, Yinping & Wang, Xin & Chen, Qun, 2013. "Ideal thermal conductivity of a passive building wall: Determination method and understanding," Applied Energy, Elsevier, vol. 112(C), pages 967-974.
    4. Yang, Liu & Yan, Haiyan & Lam, Joseph C., 2014. "Thermal comfort and building energy consumption implications – A review," Applied Energy, Elsevier, vol. 115(C), pages 164-173.
    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. García Kerdan, Iván & Raslan, Rokia & Ruyssevelt, Paul, 2016. "An exergy-based multi-objective optimisation model for energy retrofit strategies in non-domestic buildings," Energy, Elsevier, vol. 117(P2), pages 506-522.
    7. Milan, Christian & Bojesen, Carsten & Nielsen, Mads Pagh, 2012. "A cost optimization model for 100% renewable residential energy supply systems," Energy, Elsevier, vol. 48(1), pages 118-127.
    8. Harmathy, Norbert & Magyar, Zoltán & Folić, Radomir, 2016. "Multi-criterion optimization of building envelope in the function of indoor illumination quality towards overall energy performance improvement," Energy, Elsevier, vol. 114(C), pages 302-317.
    9. Evins, Ralph, 2013. "A review of computational optimisation methods applied to sustainable building design," Renewable and Sustainable Energy Reviews, Elsevier, vol. 22(C), pages 230-245.
    10. Nguyen, Anh-Tuan & Reiter, Sigrid & Rigo, Philippe, 2014. "A review on simulation-based optimization methods applied to building performance analysis," Applied Energy, Elsevier, vol. 113(C), pages 1043-1058.
    11. Ascione, Fabrizio & De Masi, Rosa Francesca & de Rossi, Filippo & Ruggiero, Silvia & Vanoli, Giuseppe Peter, 2016. "Optimization of building envelope design for nZEBs in Mediterranean climate: Performance analysis of residential case study," Applied Energy, Elsevier, vol. 183(C), pages 938-957.
    12. Fong, K.F. & Lee, C.K., 2012. "Towards net zero energy design for low-rise residential buildings in subtropical Hong Kong," Applied Energy, Elsevier, vol. 93(C), pages 686-694.
    13. Lin, Yu-Hao & Tsai, Kang-Ting & Lin, Min-Der & Yang, Ming-Der, 2016. "Design optimization of office building envelope configurations for energy conservation," Applied Energy, Elsevier, vol. 171(C), pages 336-346.
    14. Corrente, Salvatore & Figueira, José Rui & Greco, Salvatore & Słowiński, Roman, 2017. "A robust ranking method extending ELECTRE III to hierarchy of interacting criteria, imprecise weights and stochastic analysis," Omega, Elsevier, vol. 73(C), pages 1-17.
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