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Green Buildings and Renewable Energy pp 349–370Cite as

Assessing Optimal U-value in Residential Buildings in Temperate Climate Conditions Considering Massive Dynamic Simulation and Statistical Uncertainty

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Part of the book series: Innovative Renewable Energy ((INREE))

Abstract

This paper focuses on an algorithmic approach to building design, based on the environmental and technological vision to the performance-driven design methodology. The performed analysis concerns to the development of an algorithm with the aim of optimizing, through dynamic energy simulation, the energy and technological definition of a building envelope, in order to minimize energy needs of sample residential buildings including a simple economic analysis including insulation costs and expected energy needs. The analysis has been done taking into account two different conditions: winter and summer seasons. In order to reach the objective, a support code in Python has been implemented to change dynamically the input data used in EnergyPlus, varying the scope of some boundary conditions that play a fundamental role in the envelope thermal design and affect the U-value. The approach and the code have been checked on a sample residential unit of about 70 m2 located in Torino Caselle. The considered input variables are the thickness of the insulation layer, the activation of the CNV (controlled natural ventilation) in summer, and the windows U-value. The proposed methodological approach and the developed script are applicable to different residential buildings according to a scalable vision and may hence constitute a first step towards the definition of an innovative tool to improve performances since early-design phases.

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Abbreviations

BIM:

Building information modelling

CNV:

Control natural ventilation

EAM:

Energy analysis model

RMSE:

Root mean square error

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Acknowledgments

This research was funded by the University Grant 59_ATEN_RSG16CHG. Furthermore, the proposed approach was tested during the Course ICT in Building Design, Master Degree in ICT for Smart Society, Politecnico di Torino, Italy, A.Y. 2018-19, with the support of the LASTIN laboratory, Microclimate section, DAD department.

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Authors and Affiliations

  1. Department of Architecture and Design, Politecnico di Torino, Torino, Italy

    Giacomo Chiesa & Mario Grosso

  2. Department DIST, Politecnico di Torino, Torino, Italy

    Andrea Acquaviva

  3. Department DAUIN and EClab, Politecnico di Torino, Torino, Italy

    Lorenzo Bottaccioli

  4. Department DET, Politecnico di Torino, Torino, Italy

    Francesca Pacella, Annalisa Pelati & Stefania Titone

Authors
  1. Giacomo Chiesa
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  2. Andrea Acquaviva
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  3. Lorenzo Bottaccioli
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  4. Mario Grosso
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  5. Francesca Pacella
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  6. Annalisa Pelati
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  7. Stefania Titone
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Corresponding author

Correspondence to Giacomo Chiesa .

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Editors and Affiliations

  1. World Renewable Energy Congress, Brighton, UK

    Ali Sayigh

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Chiesa, G. et al. (2020). Assessing Optimal U-value in Residential Buildings in Temperate Climate Conditions Considering Massive Dynamic Simulation and Statistical Uncertainty. In: Sayigh, A. (eds) Green Buildings and Renewable Energy. Innovative Renewable Energy. Springer, Cham. https://doi.org/10.1007/978-3-030-30841-4_25

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  • DOI: https://doi.org/10.1007/978-3-030-30841-4_25

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