Reducing the Performance Gap by Analysing Specific Combiantions of Occupant and Building Characteristics

The energy saving policies of governments are not resulting in the energy saving they were aiming for[1]. Theoretical energy saving predictions are an important and frequently used tool for policy makers to develop energy saving policies and to set energy saving targets. Majcen et al. [2] showed a discrepancy between actual and theoretical energy consumption. The existence of the energy performance gap means that policy makers base their policies on assumptions that are not always right. It is expected that a significant part of the performance gap can be explained by the occupant behaviour, therefore a better insight in the influence of occupant behaviour on actual residential energy consumption is required. In this paper a method is introduced to analyse the influence of occupant behaviour on residential energy consumption, based on the principle that if occupant behaviour is studied also the building characteristics should be taken into account. In this paper a data analysis is executed with the use of a large building characteristics database (SHAERE - over 2 million cases), occupant data (Statistics Netherlands - entire Dutch population) and energy data (Statistics Netherlands – entire Dutch population). Although the results of the executed analysis are not conclusive, several important factors were found for further research. Firstly, the building and occupant cluster variables should be created with great care since they are one of the determining factors for correct function of the method. Secondly the quality of the dataset is of major importance for the final result. Finally, for further research it is advised to execute this method on other datasets, and compare the results in order to define which aspects are most important for applying this method.