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Parametric Optimization of Window-to-Wall Ratio for Passive Buildings Adopting A Scripting Methodology to Dynamic-Energy Simulation

Author

Listed:
  • Giacomo Chiesa

    (Department of Architecture and Design, Politecnico di Torino, Turin 10125, Italy)

  • Andrea Acquaviva

    (Department DIST, Politecnico di Torino, Turin 10125, Italy)

  • Mario Grosso

    (Department of Architecture and Design, Politecnico di Torino, Turin 10125, Italy)

  • Lorenzo Bottaccioli

    (Department DAUIN, Politecnico di Torino, Turin 10138, Italy)

  • Maurizio Floridia

    (ICT for Smart Societies, Department DET, Politecnico di Torino, Turin 10138, Italy)

  • Edoardo Pristeri

    (ICT for Smart Societies, Department DET, Politecnico di Torino, Turin 10138, Italy)

  • Edoardo Maria Sanna

    (ICT for Smart Societies, Department DET, Politecnico di Torino, Turin 10138, Italy)

Abstract

Counterbalancing climate change is one of the biggest challenges for engineers around the world. One of the areas in which optimization techniques can be used to reduce energy needs, and with that the pollution derived from its production, is building design. With this study of a generic office located both in a northern country and in a temperate/Mediterranean site, we want to introduce a coding approach to dynamic energy simulation, able to suggest, from the early-design phases when the main building forms are defined, optimal configurations considering the energy needs for heating, cooling and lighting. Generally, early-design considerations of energy need reduction focus on the winter season only, in line with the current regulations; nevertheless a more holistic approach is needed to include other high consumption voices, e.g., for space cooling and lighting. The main considered design parameter is the WWR (window-to-wall ratio), even if further variables are considered in a set of parallel analyses (level of insulation, orientation, activation of low-cooling strategies including shading devices and ventilative cooling). Finally, the effect of different levels of occupancy was included in the analysis to regress results and compare the WWR with corresponding heating and cooling needs. This approach is adapted to Passivhaus design optimization, working on energy need minimisation acting on envelope design choices. The results demonstrate that it is essential to include, from the early-design configurations, a larger set of variables in order to optimize the expected energy needs on the basis of different aspects (cooling, heating, lighting, design choices). Coding is performed using Python scripting, while dynamic energy simulations are based on EnergyPlus.

Suggested Citation

  • Giacomo Chiesa & Andrea Acquaviva & Mario Grosso & Lorenzo Bottaccioli & Maurizio Floridia & Edoardo Pristeri & Edoardo Maria Sanna, 2019. "Parametric Optimization of Window-to-Wall Ratio for Passive Buildings Adopting A Scripting Methodology to Dynamic-Energy Simulation," Sustainability, MDPI, vol. 11(11), pages 1-30, May.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:11:p:3078-:d:235948
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    References listed on IDEAS

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    Cited by:

    1. Mamdooh Alwetaishi & Omrane Benjeddou, 2021. "Impact of Window to Wall Ratio on Energy Loads in Hot Regions: A Study of Building Energy Performance," Energies, MDPI, vol. 14(4), pages 1-15, February.
    2. Qiong He & S. Thomas Ng & Md. Uzzal Hossain & Martin Skitmore, 2019. "Energy-Efficient Window Retrofit for High-Rise Residential Buildings in Different Climatic Zones of China," Sustainability, MDPI, vol. 11(22), pages 1-19, November.
    3. Pajek, Luka & Košir, Mitja, 2021. "Strategy for achieving long-term energy efficiency of European single-family buildings through passive climate adaptation," Applied Energy, Elsevier, vol. 297(C).
    4. Martina Dell’Unto & Louise-Nour Sassenou & Lorenzo Olivieri & Francesca Olivieri, 2023. "Technical Feasibility for the Boosting of Positive Energy Districts (PEDs) in Existing Mediterranean Districts: A Methodology and Case Study in Alcorcón, Spain," Sustainability, MDPI, vol. 15(19), pages 1-21, September.
    5. Giacomo Chiesa & Francesca Fasano & Paolo Grasso, 2021. "A New Tool for Building Energy Optimization: First Round of Successful Dynamic Model Simulations," Energies, MDPI, vol. 14(19), pages 1-20, October.
    6. ChungYeon Won & SangTae No & Qamar Alhadidi, 2019. "Factors Affecting Energy Performance of Large-Scale Office Buildings: Analysis of Benchmarking Data from New York City and Chicago," Energies, MDPI, vol. 12(24), pages 1-17, December.
    7. Thomas Auer & Philipp Vohlidka & Christine Zettelmeier, 2020. "The Right Amount of Technology in School Buildings," Sustainability, MDPI, vol. 12(3), pages 1-19, February.
    8. Henriqueta Teixeira & Maria da Glória Gomes & António Moret Rodrigues & Júlia Pereira, 2021. "In-Service Thermal and Luminous Performance Monitoring of a Refurbished Building with Solar Control Films on the Glazing System," Energies, MDPI, vol. 14(5), pages 1-23, March.
    9. Yao Lu & Hankun Lin & Siwei Liu & Yiqiang Xiao, 2019. "Nonuniform Woven Solar Shading Screens: Shading, Mechanical, and Daylighting Performance," Sustainability, MDPI, vol. 11(20), pages 1-19, October.

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