Visible to the public Privacy-preserving consensus-based energy management in smart grid

TitlePrivacy-preserving consensus-based energy management in smart grid
Publication TypeConference Paper
Year of Publication2017
AuthorsZhao, C., He, J., Cheng, P., Chen, J.
Conference Name2017 IEEE Power Energy Society General Meeting
KeywordsAlgorithm design and analysis, convergence, Energy management, Human Behavior, human factors, privacy, pubcrawl, resilience, Resiliency, Scalability, Sensitivity, smart grid consumer privacy, Smart Grid Privacy, Smart grids, Topology

This paper investigates the privacy-preserving problem of the distributed consensus-based energy management considering both generation units and responsive demands in smart grid. First, we reveal the private information of consumers including the electricity consumption and the sensitivity of the electricity consumption to the electricity price can be disclosed without any privacy-preserving strategy. Then, we propose a privacy-preserving algorithm to preserve the private information of consumers through designing the secret functions, and adding zero-sum and exponentially decreasing noises. We also prove that the proposed algorithm can preserve the privacy while keeping the optimality of the final state and the convergence performance unchanged. Extensive simulations validate the theoretical results and demonstrate the effectiveness of the proposed algorithm.

Citation Keyzhao_privacy-preserving_2017