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Application of a staged automated calibration methodology to a partially-retrofitted university building energy model
Zuhaib, Sheikh; Hajdukiewicz, Magdalena; Goggins, Jamie
Deep-retrofit planning for existing buildings demands high accuracy in energy modelling prediction that minimises the gap between actual and simulated scenarios. A large set of interacting variables and uncertainties in energy performance modelling causes perturbations that can be minimised via model calibration. In this work, a novel multi-stage automated calibration methodology was developed using a case study of a partially-retrofitted university building (>35 yrs old) in Ireland. The methodology enables the analysis of models for Indoor Environmental Quality (IEQ) variables along with energy demand. Due to the higher number of uncertainties in the model, a sensitivity analysis was conducted on the model that is both calibrated and validated as per ASHRAE Guide 14 indices of Cv(RMSE) and NMBE. The calibration process was automated using the optimisation algorithm NSGA-II with two sets of reference data i.e. monthly utility and hourly indoor air temperature. Results demonstrate that using only utility data for calibration did not result in accurate predictions of the thermal environment; thus, a second stage was used to improve the model prediction giving a Cv(RMSE)hourly = 17.0–25.5% and NMBEhourly = 3.6–10.0% for indoor air temperature across multiple zones. This paper demonstrates an effective staged approach for creating calibrated models of old buildings under high uncertainty that can be used to influence large-scale decision making for retrofits focused on improving indoor environment quality and energy performance. The authors would like to acknowledge financial support from Science Foundation Ireland (Grant No. 13/CDA/2200) and European Union’s Horizon 2020 Built2Spec project (Grant No. 637221). The authors would also like to thank all the participants of survey from the case study building and the Buildings & Estates Office at NUI Galway for facilitating the data required in this research. The authors would also like to acknowledge Prof Corey Griffin for his input into the early stages of model development. 2021-07-10
Keyword(s): Calibration; Sensitivity analysis; Energy efficiency; Building energy model; Optimisation; Retrofit; Simulation
Publication Date:
2019
Type: Journal article
Peer-Reviewed: Yes
Language(s): English
Contributor(s): Science Foundation Ireland; Horizon 2020
Institution: NUI Galway
Publisher(s): Elsevier
File Format(s): application/pdf
First Indexed: 2019-09-20 06:39:20 Last Updated: 2019-09-20 06:39:20