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Building model calibration using energy and environmental data

Lookup NU author(s): Dr Mohammad Royapoor, Professor Tony Roskilly

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This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).


Abstract

A large number of randomly interacting variables combine to dictate the energy performance of a building. Building energy simulation models attempt to capture these perturbations as accurately as possible. The prediction accuracy of building energy models can now be better examined given the widespread availability of environmental and energy monitoring equipment and reduced data storage costs. In this paper a set of two calibrated environmental sensors together with a weather station are deployed in a 5 storey office building to examine the accuracy of an EnergyPlus virtual building model. Using American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE) Guide 14 indices the model was calibrated to achieve Mean Bias Error (MBE) values within ±5% and Cumulative Variation of Root Mean Square Error (CV(RMSE)) values below 10%. The calibrated EnergyPlus model was able to predict the hourly annual space air temperatures with an accuracy of ±1.5°C for 99.5% and an accuracy of ±1°C for 93.2% of the time.


Publication metadata

Author(s): Royapoor M, Roskilly T

Publication type: Article

Publication status: Published

Journal: Energy and Buildings

Year: 2015

Volume: 94

Pages: 109-120

Print publication date: 01/05/2015

Online publication date: 28/02/2015

Acceptance date: 21/02/2015

ISSN (print): 0378-7788

ISSN (electronic): 1872-6178

Publisher: Elsevier

URL: http://dx.doi.org/10.1016/j.enbuild.2015.02.050

DOI: 10.1016/j.enbuild.2015.02.050


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