On March 27, 2017, Dominik Engel gave an invited talk on “The Interplay of Data Resolution and Privacy in Smart Metering” at Cornell University by invitation of Prof. Stephen Wicker.

The change from traditional energy grids to become so-called Smart Grids is an enabler of the important societal goal to turn from fossil energy to renewable energy sources. The vision is to build intelligent energy grids that harness the insights of information and communication technology (ICT) to allow widespread integration of renewable energy sources, self-healing grids, connection of smart homes and smart electric vehicles, synchronization of demand and response, and many other use cases. Spreading such Smart Grid technologies will be inherently difficult without addressing user concerns regarding privacy issues. These concerns are especially pronounced when it comes to smart metering. Through smart metering load profiles are measured per household. It has been shown that personal data can be inferred from these load profiles, which has led to privacy concerns.

Surprisingly, the debate regarding the impact on privacy of measurements in smart metering has been largely led without taking the issue of resolution into consideration. The influence of data resolution on privacy impact can be seen in other domains, such as video surveillance, where resolution is a critical factor.

In this talk, first the impact of data granularity on edge detection, a first step in appliance detection, is reviewed. Based on these insights, a method for generating multi-resolution representation of load profiles by using the wavelet transform is presented. By using a hierarchical keying scheme and different keys in the different keys on the various resolutions, users can decide which party can access their load profile at which resolution. Finally, open issues and further research directions are discussed.