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A New Tool for Building Energy Optimization: First Round of Successful Dynamic Model Simulations

Author

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  • Giacomo Chiesa

    (Department of Architecture and Design, Politecnico di Torino, Viale PierAndrea Mattioli 39, 10125 Turin, Italy
    These authors contributed equally to this work.)

  • Francesca Fasano

    (Department of Architecture and Design, Politecnico di Torino, Viale PierAndrea Mattioli 39, 10125 Turin, Italy
    These authors contributed equally to this work.)

  • Paolo Grasso

    (Department of Architecture and Design, Politecnico di Torino, Viale PierAndrea Mattioli 39, 10125 Turin, Italy
    These authors contributed equally to this work.)

Abstract

Several tools and pieces of software support building energy modelling for optimization, certification and comparisons of different scenarios and usages. Nevertheless, the consistent rise in accessible computational power and the expansion of ICT are pushing the development of new software functionalities and tools able to support cross-disciplinary work on smart building optimization. This paper introduces a new platform (under development) that combines the EnergyPlus dynamic simulation tool with extra-functionalities and pre-defined usage scenarios based on automatic actions to manage massive simulations and correlation analyses. The tool’s utility was tested in three experiments, with goals that we consider to be fundamental requirements: comparing simple retrofit actions to reduce net energy needs; analyzing the free-running potential of a demo building and the impacts of different low-energy technologies in terms of increasing thermal comfort (shading and ventilative cooling); and comparing measured sensor data indicators with simulated ones under real weather conditions for model verification. The results demonstrate the ability of the tool to automatically generate hundreds of EnergyPlus input building models by acting on building geometry; we focused on the most common uses for parametric dynamic simulations. Additionally, the way in which the tool combines the automatic modification of the building’s design and the parallel launching of multiple simulations allows the labor to be reduced. The user can execute complex tasks without spending any time working with model editing software and aggregating the results from multiple simulations.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:19:p:6429-:d:651900
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    References listed on IDEAS

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    1. Pasichnyi, Oleksii & Wallin, Jörgen & Kordas, Olga, 2019. "Data-driven building archetypes for urban building energy modelling," Energy, Elsevier, vol. 181(C), pages 360-377.
    2. Germán Campos Gordillo & Germán Ramos Ruiz & Yves Stauffer & Stephan Dasen & Carlos Fernández Bandera, 2020. "EplusLauncher: An API to Perform Complex EnergyPlus Simulations in MATLAB ® and C#," Sustainability, MDPI, vol. 12(2), pages 1-14, January.
    3. 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.
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    Cited by:

    1. Kotarela, Faidra & Kyritsis, Anastasios & Agathokleous, Rafaela & Papanikolaou, Nick, 2023. "On the exploitation of dynamic simulations for the design of buildings energy systems," Energy, Elsevier, vol. 271(C).
    2. Martin, Rit & Arthur, Thomas & Jonathan, Villot & Mathieu, Thorel & Enora, Garreau & Robin, Girard, 2024. "SHAPE: A temporal optimization model for residential buildings retrofit to discuss policy objectives," Applied Energy, Elsevier, vol. 361(C).

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