On Privacy Preservation of Distributed Energy Resource Optimization in Power Distribution Networks

The exploding deployment of distributed energy resources (DERs) brings unprecedented challenges to the optimization of large-scale power distribution networks-numerous grid-tied devices pose severe control scalability crises. Besides, the exposure of private DER data, such as energy generation and consumption profiles, is leading to prevalent customer privacy breaches. Despite the importance, research on privacy-preserving DER control in a fully scalable manner is still lacking. To fill this gap, a hierarchical DER aggregation and control framework is first developed to achieve scalability over a large DER population size. Second, a novel privacy-preserving optimization algorithm is proposed for the developed DER aggregation and control framework based on the secret sharing technique. Finally, privacy preservation guarantees of the developed algorithm are provided against honest-but-curious adversaries and external eavesdroppers. Simulations on a 13-bus test feeder demonstrate the effectiveness of the proposed approach in preserving private DER data within power distribution networks.