A Fundamental Bound on Performance of Non-Intrusive Load Monitoring with Application to Smart Meter Privacy

TL;DR

This paper establishes a fundamental lower bound on the accuracy of non-intrusive load monitoring and leverages it to design privacy-preserving load scheduling policies for smart meters.

Contribution

It introduces a theoretical bound on load monitoring accuracy and applies it to develop policies that enhance smart meter privacy.

Findings

The estimation error is lower bounded by the inverse of the cross-correlation matrix trace.

A load-scheduling policy is devised to maximize this lower bound.

The approach improves privacy by reducing load monitoring accuracy.

Abstract

We prove that the expected estimation error of non-intrusive load monitoring algorithms is lower bounded by the trace of the inverse of the cross-correlation matrix between the derivatives of the load profiles of the appliances. We use this fundamental bound to develop privacy-preserving policies. Particularly, we devise a load-scheduling policy by maximizing the lower bound on the expected estimation error of non-intrusive load monitoring algorithms.