Privacy of Real-Time Pricing in Smart Grid

TL;DR

This paper introduces a Blowfish privacy mechanism for smart grid real-time pricing, using a Markov model and perturbation algorithm to protect household occupancy privacy while maintaining data utility.

Contribution

It proposes a novel privacy-preserving algorithm for real-time electricity rates based on Blowfish privacy and a Markov model of consumption.

Findings

The algorithm effectively protects occupancy privacy.

Performance is comparable to existing solutions.

Tested on household occupancy data.

Abstract

Installing smart meters to publish real-time electricity rates has been controversial while it might lead to privacy concerns. Dispatched rates include fine-grained data on aggregate electricity consumption in a zone and could potentially be used to infer a household's pattern of energy use or its occupancy. In this paper, we propose Blowfish privacy to protect the occupancy state of the houses connected to a smart grid. First, we introduce a Markov model of the relationship between electricity rate and electricity consumption. Next, we develop an algorithm that perturbs electricity rates before publishing them to ensure users' privacy. Last, the proposed algorithm is tested on data inspired by household occupancy models and its performance is compared to an alternative solution.