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

Author:

Angelotti Adriana1ORCID,Mazzarella Livio1,Cornaro Cristina2ORCID,Frasca Francesca3ORCID,Prada Alessandro4ORCID,Baggio Paolo4ORCID,Ballarini Ilaria5ORCID,De Luca Giovanna5,Corrado Vincenzo5ORCID

Affiliation:

1. Dipartimento di Energia, Politecnico di Milano, 20156 Milano, Italy

2. Dipartimento di Ingegneria dell’Impresa, Università degli Studi di Roma Tor Vergata, 00133 Roma, Italy

3. Dipartimento di Fisica, Università La Sapienza, 00185 Roma, Italy

4. Dipartimento di Ingegneria Civile, Ambientale e Meccanica, Università di Trento, 38122 Trento, Italy

5. 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.

Publisher

MDPI AG

Subject

Energy (miscellaneous),Energy Engineering and Power Technology,Renewable Energy, Sustainability and the Environment,Electrical and Electronic Engineering,Control and Optimization,Engineering (miscellaneous),Building and Construction

Reference38 articles.

1. ENEA (2021). Rapporto Annuale 2021, ENEA. (In Italian).

2. ASHRAE (2002). Measurement of Energy and Demand Saving, ASHRAE.

3. A review of methods to match building energy simulation models to measured data;Coakley;Renew. Sustain. Energy Rev.,2014

4. Methodologies and advancements in the calibration of building energy models;Fabrizio;Energies,2015

5. Validation of dynamic hygrothermal simulation models for historical buildings: State of the art, research challenges and recommendations;Leonforte;Build. Environ.,2020

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