A consensus-based privacy-preserving energy management strategy for microgrids with event-triggered scheme. (October 2022)

• Record Type: Journal Article
• Authors: Yan, Linfang; Chen, Xia; Chen, Yin
• Is Part Of: International journal of electrical power & energy systems. Volume 141(2022)
• Publication Date: 2022-10
• Subjects: Distributed energy management -- Microgrids -- Privacy-preserving -- Event-triggered scheme -- Differential privacy; Electrical engineering -- Periodicals; Electric power systems -- Periodicals; Électrotechnique -- Périodiques; Réseaux électriques (Énergie) -- Périodiques; Electric power systems; Electrical engineering; Periodicals; 621.3
• DOI: 10.1016/j.ijepes.2022.108198
• Languages: English
• ISSNs: 0142-0615

Abstract

Highlights: This paper investigates the privacy disclosure under the consensus-based distributed algorithm in the microgrid and provides the analysis of privacy disclosure on both supply and demand sides in the distributed energy management. A novel consensus-based privacy-preserving strategy with event-triggered scheme is developed to protect the privacy and reduce the consumption of network resources simultaneously. The convergence analysis, accuracy analysis and differential privacy analysis are all made to guarantee the algorithm's sufficiency. Besides, the trade-off between the privacy level and convergence accuracy is also discussed. Abstract: In terms of the distributed energy management (DEM) in microgrids, increasing distributed generators and users will bring tremendous data transmitted in the communication network. Considering the data security and the computation efficiency, protecting the participants' privacy and saving the communication network resources are essential. This paper proposes a consensus-based distributed privacy-preserving energy management strategy with the event-triggered scheme to achieve privacy-preserving and network resource-saving simultaneously. Firstly, the DEM in microgrids is formulated as a social welfare maximization problem. Then the privacy disclosure of both generators and consumers under the consensus-based distributed control strategy is analyzed. Next, a consensus-based privacy-preserving algorithm using differential privacy is designed to protect private information. An event-triggered scheme is applied to the strategy to save network resources. Besides, theoretical analysis, including convergence, accuracy and differential privacy, is presented to guarantee the algorithm's sufficiency. The trade-off between the accuracy and privacy level is also investigated. Finally, simulation results demonstrate the effectiveness of the proposed algorithm.