Abstract
Smart meters are devices that facilitate the collection of energy consumption data in almost real-time for individual users. Smart grids rely on smart meters for real-time data on energy consumption to manage demand and supply effectively. However, the use of smart meters raises concerns about privacy, as sensitive information about individual users’ routines and behavior can be revealed. And the collection of this data enables utility companies to track and analyze energy usage patterns of individual users, which may also reveal sensitive information about their lifestyle habits. To address this issue, we propose a Φ-differential privacy scheme to safeguard users’ privacy in datasets by incorporating differential privacy and adding noise. In this paper, we also propose an incentive-based demand response (IDR) scheme to reward customers for reducing energy usage and sharing honest data in response to demand response requests. Overall, our paper emphasizes the importance of addressing privacy concerns in smart grid operations and proposes solutions to enhance the privacy of individual users while leveraging the benefits of smart meters and differential privacy for efficient energy management.
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Acknowledgements
The project was supported by the national natural science foundation of China (Project No. 62302211）, Hillstone networks project of network security (Project No. 2022HS038) and Jiangsu Province Engineering Research Center of IntelliSense Technology and System and the Innovative Training Program for College Students of Jiangsu Province (Grant No. 2274108123021).
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Yao, X., Wu, Y., Su, J., Huang, R., Tian, Y. (2024). A Φ-Differential Privacy Scheme for Incentive-Based Demand Response in Smart Grid. In: Li, S. (eds) Computational and Experimental Simulations in Engineering. ICCES 2023. Mechanisms and Machine Science, vol 146. Springer, Cham. https://doi.org/10.1007/978-3-031-44947-5_43
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DOI: https://doi.org/10.1007/978-3-031-44947-5_43
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