Abstract
This paper examines how calibration performs under different levels of uncertainty in model input data. It specifically assesses the efficacy of Bayesian calibration to enhance the reliability of EnergyPlus models. A Bayesian approach can quantify uncertainty in uncertain parameters while updating their values given measurement data. We assess the efficacy of Bayesian calibration under a controlled virtual-reality setup, which enables researchers to rigorously validate the accuracy of calibration results in terms of both calibration parameter values and calibrated model predictions. Case studies demonstrate the performance of Bayesian calibration of base models developed from audit data with differing levels of detail in building design, usage and operation.
Original language | English |
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Pages | 1690-1697 |
Number of pages | 8 |
Publication status | Published - 2013 |
Externally published | Yes |
Event | 13th Conference of the International Building Performance Simulation Association, BS 2013 - Chambery, France Duration: 2013 Aug 26 → 2013 Aug 28 |
Conference
Conference | 13th Conference of the International Building Performance Simulation Association, BS 2013 |
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Country/Territory | France |
City | Chambery |
Period | 13/8/26 → 13/8/28 |
ASJC Scopus subject areas
- Civil and Structural Engineering
- Building and Construction
- Modelling and Simulation