Preserving privacy in Distributed Energy Management

The smart power grid transforms into a distributed system of manifold stakeholders by integrating communication technology into the former static power grid. Distributed Energy Management (DEM) will play a vital role in future demand supply matching. An important and often overlooked factor in this concept is privacy. In this paper we present Priv-ADE, a privacy preserving algorithm for DEM. It utilises homomorphic encryption to privately gather aggregated data and perform energy management based on the max---min fairness principle. Simulations show that PrivADE achieves similar consumption results as two comparative approaches, while in contrast preserves privacy at all times. The computational and communicational complexity is analysed. Furthermore, the privacy concept is adopted to PowerMatcher.