Estimation of thermophysical properties
Estimation of thermophysical properties from in-situ measurements in all seasons: Quantifying and reducing errors using dynamic grey-box methods
Journal Article ‘Estimation of thermophysical properties from in-situ measurements in all seasons: Quantifying and reducing errors using dynamic grey-box methods’ co-authored by Virginia Gori, Research Associate at the RCUK Centre for Energy Epidemiology (CEE) and Clifford A. Elwell, Lecturer, UCL Energy Institute. Published in ‘Energy and Buildings’, volume 167, pg 290-300.
- U-values and systematic errors were estimated from data monitored across seasons
- Uniform, static and dynamic error quantification methods were compared and discussed
- A method for the quantification of systematic error for dynamic analysis was proposed
- The dynamic method always reduced the error on U-value compared to the static method
- Dynamic are more robust than static methods to low average temperature differences.
Robust characterisation of the thermal performance of buildings from in-situ measurements requires error analysis to evaluate the certainty of estimates. A method for the quantification of systematic errors on the thermophysical properties of buildings obtained using dynamic grey-box methods is presented, and compared to error estimates from the average method. Different error propagation methods (accounting for equipment uncertainties) were introduced to reflect the different mathematical description of heat transfer in the static and dynamic approaches.
Thermophysical properties and their associated errors were investigated using two case studies monitored long term. The analysis showed that the dynamic method (and in particular a three thermal resistance and two thermal mass model) reduced the systematic error compared to the static method, even for periods of low internal-to-external average temperature difference. It was also shown that the use of a uniform error as suggested in the ISO 9869-1:2014 Standard would generally be misrepresentative. The study highlighted that dynamic methods for the analysis of in-situ measurements may provide robust characterisation of the thermophysical behaviour of buildings and extend their application beyond the winter season in temperate climates (e.g., for quality assurance and informed decision making purposes) in support of closing the performance gap.