  The rapidly growing penetration of renewable energy resources brings
unprecedented challenges to power distribution networks - management of a large
population of grid-tied controllable devices encounters control scalability
crises and potential end-user privacy breaches. Despite the importance,
research on privacy preservation of distributed energy resource (DER) control
in a fully scalable manner is lacked. To fill the gap, this paper designs a
novel decentralized privacy-preserving DER control framework that 1) achieves
control scalability over DER population and heterogeneity; 2) eliminates
peer-to-peer communications and secures the privacy of all participating DERs
against various types of adversaries; and 3) enjoys higher computation
efficiency and accuracy compared to state-of-the-art privacy-preserving
methods. A strongly coupled optimization problem is formulated to control the
power consumption and output of DERs, including solar photovoltaics and energy
storage systems, then solved using the projected gradient method. Cloud
computing and secret sharing are seamlessly integrated into the proposed
decentralized computing to achieve privacy preservation. Simulation results
prove the capabilities of the proposed approach in DER control applications.
