Consumer privacy on distributed energy markets

Abstract

Recently, several privacy-enhancing technologies for smart grids have been proposed. However, most of these solutions presume the cooperation of all smart grid participants. Hence, the privacy protection of consumers depends on the willingness of the suppliers to deploy privacy-enhancing technologies. Since electrical energy is essential for our modern life, it is impossible for consumers to opt out. We propose a novel consumer-only (do-it-yourself) privacy-enhancing approach under the assumption that users can obtain their energy from multiple suppliers on a distributed market. By splitting the demand over multiple suppliers, the information each of them can collect about a single consumer is reduced. In this context, we suggest two different buying strategies: a time and a sample diversification strategy. To measure their provided level of privacy protection, we introduce a new indistinguishability metric λ-Indistinguishability (λ-IND) that measures how relative consumption changes can be hidden in the total consumption. We evaluate the presented strategies with λ-IND and derive first privacy boundaries. The evaluation of our buying strategies on real-world energy data sets indicates their ability to hide load profiles of privacy sensitive appliances at low communication and computational overhead.