Robustness of a regression approach, aimed for calibration of whole building energy simulation tools

• Onsite monitoring of supplied energy and temperatures in two multifamily buildings.
• Used a regression approach to extract buildings thermal performance parameters.
• These parameters are found to be robust and agree well with theory.

An approach, able to easily and effectively integrate field measured data in whole building energy simulation (BES) models is crucial to increase simulation accuracy for existing buildings. In this paper, the robustness of a linear regression method for extracting transmission losses above ground (including air leakage) and ground heat loss parameters are analyzed. The regression method is evaluated on two documented and monitored multifamily buildings with mechanical supply and exhaust ventilation systems, with and without heat recovery.The obtained results are found to be robust, with variations less than 2% in the extracted estimates of transmission losses above ground (including air leakage) and with a high goodness of fit (R2 > 0.96) against measured data from two years. In addition, the estimations of the buildings ground heat loss were in good agreement with calculations in accordance with EN ISO 13370:2007. The high quality output from the used regression method serves as good prerequisites for the method to be used in conjunction with BES models to aid the analyst in a BES calibration process.