The influence of occupant behaviour on the energy performance of single office space with adaptive facades: simulation versus measured data

Luna-Navarro, Alessandra; Hensen, Jlm Jan; Law, Alistair; Anselmo, Francesco; Overend, Mauro

doi:10.26868/25222708.2021.30525

Cited by 1 publication

(1 citation statement)

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“…BPS tools are software tools for predicting building performance by dynamically solving a set of mathematical equations. The main barriers to an accurate performance prediction of adaptive building envelopes in BPS tools are: (i) the limited modelling capabilities of existing BPS tools in simulating different types and ranges of control algorithms, on which the performance of adaptive building envelopes during operation largely depends (Loonen et al, 2017), (ii) the limited integration of multi-domain influences (Tabadkani, Tsangrassoulis, Roetzel, & Li, 2020) and (iii) the lack of occupant behaviour models that can successfully estimate the impact of users (Luna-Navarro, Gaetani, Anselmo, Law, & Overend, 2021). This limits the capability of BPS tools to adequately capture the influence of the control algorithm on the dynamic behaviour of adaptive building envelopes, which in turn increases the uncertainty about accurately predicting adaptive building envelope performance.…”

Section: Introductionmentioning

confidence: 99%

Empirical validation of co-simulation models for adaptive building envelopes

Borkowski

Luna-Navarro

Michael

et al. 2022

JFDE

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The thermal performance of adaptive building envelopes can be evaluated using building performance simulation tools. Simulation capabilities and accuracy in predicting the dynamic behaviour of adaptive building envelopes can be enhanced through co-simulation. However, it is unclear how accurately co-simulation can predict the performance of adaptive building envelopes and how the accuracy of adaptive building envelope models created in co-simulation setups can be assessed and validated. Therefore, this study presents new evidence on the empirical validation of co-simulation setups for adaptive building envelopes by establishing an assessment framework to determine the extent to which they can accurately represent the real world. The framework was applied to a case study to validate a co-simulation setup for a blind automation system using monitored data from MATELab, a full-scale outdoor test facility with realistic indoor and outdoor conditions. The validation of the co-simulation model of MATELab resulted in a median CV-RMSE index, a measure of model accuracy, of 5.9%. This indicates that the simulated data points have a small variance relative to the measured data points, showing a good model fit. In the future, modellers from the façade community can use the assessment framework for their co-simulation setups.

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Section: Introductionmentioning

confidence: 99%