Influence of data granularity on nonintrusive appliance load monitoring

Abstract

Decreasing time resolution is the simplest possible privacy enhancing technique for energy consumption data. However, its impact on privacy analyses of load signals has never been studied systematically. Non-intrusive appliance load monitoring algorithms (NIALM) have originally been designed for energy disaggregation for subsequent energy feedback. However, the information on appliance use may also be misused for the extraction of personal information. In this work, the effect of decreasing the time resolution in the usual first step, namely edge detection, is studied. It is shown that event values can be estimated rather reliably, but the detection rate of events significantly decreases with increasing measurement time interval.