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Calibrating the Dynamic Energy Simulation Model for an Existing Building: Lessons Learned from a Collective Exercise

Author

Listed:
  • Adriana Angelotti

    (Dipartimento di Energia, Politecnico di Milano, 20156 Milano, Italy)

  • Livio Mazzarella

    (Dipartimento di Energia, Politecnico di Milano, 20156 Milano, Italy)

  • Cristina Cornaro

    (Dipartimento di Ingegneria dell’Impresa, Università degli Studi di Roma Tor Vergata, 00133 Roma, Italy)

  • Francesca Frasca

    (Dipartimento di Fisica, Università La Sapienza, 00185 Roma, Italy)

  • Alessandro Prada

    (Dipartimento di Ingegneria Civile, Ambientale e Meccanica, Università di Trento, 38122 Trento, Italy)

  • Paolo Baggio

    (Dipartimento di Ingegneria Civile, Ambientale e Meccanica, Università di Trento, 38122 Trento, Italy)

  • Ilaria Ballarini

    (Dipartimento Energia, Politecnico di Torino, 10129 Torino, Italy)

  • Giovanna De Luca

    (Dipartimento Energia, Politecnico di Torino, 10129 Torino, Italy)

  • Vincenzo Corrado

    (Dipartimento Energia, Politecnico di Torino, 10129 Torino, Italy)

Abstract

Calibration of the existing building simulation model is key to correctly evaluating the energy savings that are achievable through retrofit. However, calibration is a non-standard phase where different approaches can possibly lead to different models. In this study, an existing residential building is simulated in parallel by four research groups with different dynamic simulation tools. Manual/automatic methodologies and basic/detailed measurement data sets are used. The calibration is followed by a validation on two evaluation periods. Monitoring data concerning the windows opening by the occupants are used to analyze the calibration outcomes. It is found that for a good calibration of a model of a well-insulated building, the absence of data regarding the users’ behavior is more critical than uncertainty on the envelope properties. The automatic approach is more effective in managing the model complexity and reaching a better performing calibration, as the RMSE relative to indoor temperature reaches 0.3 °C compared to 0.4–0.5 °C. Yet, a calibrated model’s performance is often poor outside the calibration period (RMSE increases up to 10.8 times), and thus, the validation is crucial to discriminate among multiple solutions and to refine them, by improving the users’ behavior modeling.

Suggested Citation

  • Adriana Angelotti & Livio Mazzarella & Cristina Cornaro & Francesca Frasca & Alessandro Prada & Paolo Baggio & Ilaria Ballarini & Giovanna De Luca & Vincenzo Corrado, 2023. "Calibrating the Dynamic Energy Simulation Model for an Existing Building: Lessons Learned from a Collective Exercise," Energies, MDPI, vol. 16(7), pages 1-24, March.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:7:p:2979-:d:1106651
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    References listed on IDEAS

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    1. Enrico Fabrizio & Valentina Monetti, 2015. "Methodologies and Advancements in the Calibration of Building Energy Models," Energies, MDPI, vol. 8(4), pages 1-27, March.
    2. Prada, A. & Gasparella, A. & Baggio, P., 2018. "On the performance of meta-models in building design optimization," Applied Energy, Elsevier, vol. 225(C), pages 814-826.
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