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Building envelope design: Multi-objective optimization to minimize energy consumption, global cost and thermal discomfort. Application to different Italian climatic zones

Author

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  • Ascione, Fabrizio
  • Bianco, Nicola
  • Maria Mauro, Gerardo
  • Napolitano, Davide Ferdinando

Abstract

The paper proposes a multi-objective optimization approach to address the energy design of the building envelope. A genetic algorithm (GA) is implemented by means of the coupling between MATLAB® and EnergyPlus to minimize primary energy consumption (PEC), energy-related global cost (GC) and discomfort hours (DH). The design variables concern the set point temperatures, the radiative properties of plasters, the thermo-physical properties of envelope components, the window type, the building orientation. The GA performs a Pareto optimization and finally two optimal solutions are recommended: the nZEB (nearly zero energy building) optimal solution, which minimizes PEC, and the cost-optimal solution, which minimizes GC. These solutions provide the optimal design strategies for the public and private stakeholders, respectively, which represent the main actors involved in building design. The approach is applied for the design of a new typical Italian residential building. Four locations are considered to investigate the typical Italian climates. The outcomes can give precious indications to rebuild the Italian residential stock with a view to energy-efficiency and cost-optimality, given that the optimal solutions provide low values of PEC – between 62.0 and 91.9 kWhp/m2a – and of GC – between 456 and 665 €/m2 – depending on the location.

Suggested Citation

  • Ascione, Fabrizio & Bianco, Nicola & Maria Mauro, Gerardo & Napolitano, Davide Ferdinando, 2019. "Building envelope design: Multi-objective optimization to minimize energy consumption, global cost and thermal discomfort. Application to different Italian climatic zones," Energy, Elsevier, vol. 174(C), pages 359-374.
    • Handle: RePEc:eee:energy:v:174:y:2019:i:c:p:359-374
    DOI: 10.1016/j.energy.2019.02.182
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    References listed on IDEAS

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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. Shi, Xing & Tian, Zhichao & Chen, Wenqiang & Si, Binghui & Jin, Xing, 2016. "A review on building energy efficient design optimization rom the perspective of architects," Renewable and Sustainable Energy Reviews, Elsevier, vol. 65(C), pages 872-884.
    3. Chen, Xi & Yang, Hongxing & Peng, Jinqing, 2019. "Energy optimization of high-rise commercial buildings integrated with photovoltaic facades in urban context," Energy, Elsevier, vol. 172(C), pages 1-17.
    4. Mostavi, Ehsan & Asadi, Somayeh & Boussaa, Djamel, 2017. "Development of a new methodology to optimize building life cycle cost, environmental impacts, and occupant satisfaction," Energy, Elsevier, vol. 121(C), pages 606-615.
    5. Baños, R. & Manzano-Agugliaro, F. & Montoya, F.G. & Gil, C. & Alcayde, A. & Gómez, J., 2011. "Optimization methods applied to renewable and sustainable energy: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(4), pages 1753-1766, May.
    6. Shen, Pengyuan & Braham, William & Yi, Yunkyu & Eaton, Eric, 2019. "Rapid multi-objective optimization with multi-year future weather condition and decision-making support for building retrofit," Energy, Elsevier, vol. 172(C), pages 892-912.
    7. Mills, Evan & Kromer, Steve & Weiss, Gary & Mathew, Paul A., 2006. "From volatility to value: analysing and managing financial and performance risk in energy savings projects," Energy Policy, Elsevier, vol. 34(2), pages 188-199, January.
    8. Kheiri, Farshad, 2018. "A review on optimization methods applied in energy-efficient building geometry and envelope design," Renewable and Sustainable Energy Reviews, Elsevier, vol. 92(C), pages 897-920.
    9. 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.
    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. Fan, Yuling & Xia, Xiaohua, 2017. "A multi-objective optimization model for energy-efficiency building envelope retrofitting plan with rooftop PV system installation and maintenance," Applied Energy, Elsevier, vol. 189(C), pages 327-335.
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