On site characterisation of the overall heat loss coefficient: Comparison of different assessment methods by a blind validation exercise on a round robin test box

Abstract Several studies have shown that the actual thermal performance of buildings after construction may deviate significantly from its performance anticipated at design stage. As a result, there is growing interest in on site testing as a means to assess real performance. The IEA EBC Annex 58-project ‘Reliable Building Energy Performance Characterisation Based on Full Scale Dynamic Measurements’ focused on on site testing and dynamic data analysis methods that can be used to characterise the actual thermal performance and energy efficiency of building components and whole buildings. The research within this project was driven by case studies. The current paper describes one of them: the thermal characterisation of a round robin test box. This test box can be seen as a scale model of a building, and was built by one of the participants. During the project, its fabric properties remained unknown to all other participants. Full scale measurements have been performed on the test box in different countries under real climatic conditions. The obtained dynamic data has been distributed to all participants who had to characterise the thermal performance of the test box’s fabric based on the provided data. The paper compares the result of different techniques, ranging from a simple quasi-stationary analysis to advanced dynamic data analysis methods, which can be used to characterise the thermal performance based on on-site collected data.

[1]  Geert Bauwens,et al.  Co-heating test: A state-of-the-art , 2014 .

[2]  Henrik Madsen,et al.  Identifying suitable models for the heat dynamics of buildings , 2011 .

[3]  Jan Carmeliet,et al.  Brick Cavity Walls: A Performance Analysis Based on Measurements and Simulations , 2007 .

[4]  A. Rabl,et al.  Energy-efficient gas-heated housing in France: predicted and observed performance , 1991 .

[5]  Henrik Madsen,et al.  Estimation of continuous-time models for the heat dynamics of a building , 1995 .

[6]  Olaf Gutschker,et al.  Parameter identification with the software package LORD , 2008 .

[7]  Henrik Madsen,et al.  Models for describing the thermal characteristics of building components , 2008 .

[8]  Henk Visscher,et al.  Theoretical vs. actual energy consumption of labelled dwellings in the Netherlands: Discrepancies and policy implications , 2013 .

[9]  M. J. Jiménez,et al.  Analysis of capabilities and limitations of the regression method based in averages, applied to the estimation of the U value of building component tested in Mediterranean weather , 2012 .

[10]  M. J. Jiménez,et al.  Application of multi-output ARX models for estimation of the U and g values of building components in outdoor testing , 2005 .

[11]  Ricardo Enríquez,et al.  Dynamic integrated method based on regression and averages, applied to estimate the thermal parameters of a room in an occupied office building in Madrid , 2014 .

[12]  Staf Roels,et al.  Highly insulated pitched roofs resilient to air flow patterns: Guidelines based on a literature review , 2016 .

[13]  Henrik Madsen,et al.  Identification of the main thermal characteristics of building components using MATLAB , 2008 .

[14]  Bernard Marie Lachal,et al.  Predicted versus observed heat consumption of a low energy multifamily complex in Switzerland based on long-term experimental data , 2004 .

[15]  Robert Lowe,et al.  Evidence for heat losses via party wall cavities in masonry construction , 2007 .