  The smart grid incentivizes distributed agents with local generation (e.g.,
smart homes, and microgrids) to establish multi-agent systems for enhanced
reliability and energy consumption efficiency. Distributed energy trading has
emerged as one of the most important multi-agent systems on the power grid by
enabling agents to sell their excessive local energy to each other or back to
the grid. However, it requests all the agents to disclose their sensitive data
(e.g., each agent's fine-grained local generation and demand load). In this
paper, to the best of our knowledge, we propose the first privacy preserving
distributed energy trading framework, Private Energy Market (PEM), in which all
the agents privately compute an optimal price for their trading (ensured by a
Nash Equilibrium), and allocate pairwise energy trading amounts without
disclosing sensitive data (via novel cryptographic protocols). Specifically, we
model the trading problem as a non-cooperative Stackelberg game for all the
agents (i.e., buyers and sellers) to determine the optimal price, and then
derive the pairwise trading amounts. Our PEM framework can privately perform
all the computations among all the agents without a trusted third party. We
prove the privacy, individual rationality, and incentive compatibility for the
PEM framework. Finally, we conduct experiments on real datasets to validate the
effectiveness and efficiency of the PEM.
