Identifying Electric Water Heaters from Low-Resolution Smart Meter Data

Despite an increasing share of heat pumps, electric water heaters are still widely used in residential applications. Their high connected load and energy consumption combined with their thermal inertia make them ideal candidates for demand response and energy saving programs. However, due to missing or outdated information about installation locations, it is difficult to run large and targeted campaigns. Thanks to an increased roll-out of advanced metering infrastructure, smart meter data is widely available, opening new opportunities to generate the missing information. In our work, we identify electric water heaters from low-resolution smart meter data with a 15-minute sampling rate and estimate their consumption using a trainingfree detection method that is easy to interpret and adapt. On a real-world data set with measurements from 1,962 meters over one year, we achieve 89.4% accuracy in detecting households with electric water heaters. We predict heating capacity with a mean absolute error of 0.9 kW. We also find that the installed electric water heaters lead to a peak demand that is 51% higher than in a setting without electric water heating, highlighting the importance of appropriate load management. Our method can be directly incorporated into existing demand response applications.