Estimating the savings potential of occupancy-based heating strategies

Because space heating causes a large fraction of energy consumed in households, occupancy-based heating systems have become more and more popular in recent years. However, there is still no practical method to estimate the potential energy savings before installing such a system. While substantial work has been done on occupancy detection, previous work does not address a combination with heating simulation in order to provide an easily applicable method to estimate this savings potential. In this paper we present such a combination of an occupancy detection algorithm based on smart electricity meter data and a building heating simulation, which only requires publicly available weather data and some relevant building characteristics. We apply our method to a dataset containing such data for several thousand households and show that when taking occupancy into account, a household can save over 9% heating energy on average, while certain groups, such as employed single-person households, can even save 14% on average. Using our approach, households with high potential for energy savings can be quickly identified and their inhabitants could be more easily convinced to adopt an occupancy-based heating strategy.