Quantifying the Utility-Privacy Tradeoff in the Smart Grid

The modernization of the electrical grid and the installment of smart meters come with many advantages to control and monitoring. However, in the wrong hands, the data might pose a privacy treat. In this paper, we consider the tradeoff between smart grid operations and the privacy of consumers. We analyze the tradeoff between smart grid operations and how often data is collected by considering a realistic direct-load control example using thermostatically controlled loads, and we give simulation results to show how its performance degrades as the sampling frequency decreases. Additionally, we introduce a new privacy metric. This privacy metric assumes a strong adversary model, and fixes a definition of a privacy breach. Then, using results from detection theory, we can give an upper bound on the adversary’s ability to enact a privacy breach, independent of the algorithm he uses. Combining these two results allows us to directly consider the tradeoff between better load control and consumer privacy.