Towards Differential Privacy-Based Online Double Auction for Smart Grid

Abstract

In this paper, to address the issue of demand response in the smart grid with island MicroGrids (MGs), we introduce an effective and secure auction market that allows electric vehicles (EVs) having surplus energy to act as sellers, and the EVs having insufficient energy in the island MGs to act as buyers. There are two primary challenges in designing an effective auction market in the smart grid. First, the auction market scheme shall be online, allowing buyers and sellers to enter the market at any time, and satisfy several critical economic properties (individual rationality, incentive compatibility, and so on.). Second, the sensitive information of participants shall be protected in the auction process. To address these challenges, we present a novel privacy-preserving online double auction scheme based on differential privacy. In our auction market, the MicroGrid Center Controller (MGCC) acts as the auctioneer, aiming at solving the social welfare maximization problem to match buyers and sellers. The principle of differential privacy is leveraged to protect the privacy of EVs’ sensitive bidding information. Via theoretical analysis, we demonstrate that our designed auction scheme satisfies both economic and privacy-preserving properties, including individual rationality, incentive compatibility, weak budget balance, and $\varepsilon $ -differential privacy. We conduct an extensive performance evaluation to measure the effectiveness of our proposed scheme. Our experimental results show that the proposed auction scheme can not only ensure the privacy of participants but also effectively facilitates demand response in the smart grid, with respect to social welfare, satisfaction ratio, social efficiency, and computational overhead.