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Research on the Electric Energy Metering Data Sharing Method in Smart Grid Based on Blockchain

Shaocheng Wu1, Honghao Liang1, Xiaowei Chen1, Tao Liu1, Junpeng Ru2,3, Qianhong Gong2,3, Jin Li2,3,*

1 Shenzhen Power Supply Co., Ltd., Shenzhen, 518001, China
2 School of Cyberspace Security, Beijing University of Posts and Telecommunications, Beijing, 100876, China
3 Key Laboratory of Trustworthy Distributed Computing and Service (BUPT), Beijing, 100876, China

* Corresponding Author: Jin Li. Email: email

Journal on Big Data 2023, 5, 57-67. https://doi.org/10.32604/jbd.2023.044257

Abstract

Enabling data sharing among smart grid power suppliers is a pressing challenge due to technical hurdles in verifying, storing, and synchronizing energy metering data. Access and sharing limitations are stringent for users, power companies, and researchers, demanding significant resources and time for permissions and verification. This paper proposes a blockchain-based architecture for secure and efficient sharing of electric energy metering data. Further, we propose a data sharing model based on evolutionary game theory. Based on the Lyapunov stability theory, the model’s evolutionary stable strategy (ESS) is analyzed. Numerical results verify the correctness and practicability of the scheme proposed in this paper, and provide a new method for realizing convenient, safe and fast data sharing.

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APA Style
Wu, S., Liang, H., Chen, X., Liu, T., Ru, J. et al. (2023). Research on the electric energy metering data sharing method in smart grid based on blockchain. Journal on Big Data, 5(1), 57-67. https://doi.org/10.32604/jbd.2023.044257
Vancouver Style
Wu S, Liang H, Chen X, Liu T, Ru J, Gong Q, et al. Research on the electric energy metering data sharing method in smart grid based on blockchain. J Big Data . 2023;5(1):57-67 https://doi.org/10.32604/jbd.2023.044257
IEEE Style
S. Wu et al., "Research on the Electric Energy Metering Data Sharing Method in Smart Grid Based on Blockchain," J. Big Data , vol. 5, no. 1, pp. 57-67. 2023. https://doi.org/10.32604/jbd.2023.044257



cc Copyright © 2023 The Author(s). Published by Tech Science Press.
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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