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Privacy-Preserving Charging Coordination Scheme for Smart Power Grids Using a Blockchain

Author

Listed:
  • Hany Habbak

    (Department of Computer Engineering and AI, Military Technical College, Cairo 11766, Egypt)

  • Mohamed Baza

    (Department of Computer Science, College of Charleston, Charleston, SC 29424, USA)

  • Mohamed M. E. A. Mahmoud

    (Department of Electrical and Computer Engineering, Tennessee Tech University, Cookeville, TN 38505, USA)

  • Khaled Metwally

    (Department of Computer Engineering and AI, Military Technical College, Cairo 11766, Egypt)

  • Ahmed Mattar

    (Department of Computer Engineering and AI, Military Technical College, Cairo 11766, Egypt)

  • Gouda I. Salama

    (Department of Computer Engineering and AI, Military Technical College, Cairo 11766, Egypt)

Abstract

With the rapid emergence of smart grids, charging coordination is considered the intrinsic actor that merges energy storage units ( ESUs ) into the grid in addition to its substantial role in boosting the resiliency and efficiency of the grid. However, it suffers from several challenges beginning with dependency on the energy service provider ( ESP ) as a single entity to manage the charging process, which makes the grid susceptible to several types of attacks such as a single point of failure or a denial-of-service attack ( DoS ). In addition, to schedule charging, the ESUs should submit charging requests including time to complete charging ( TCC ) and battery state of charge ( SoC ), which may disclose serious information relevant to the consumers. The analysis of this data could reveal the daily activities of those consumers. In this paper, we propose a privacy-preservation charging coordination scheme using a blockchain. The blockchain achieves decentralization and transparency to defeat the security issues related to centralized architectures. The privacy preservation will be fulfilled using a verifiable aggregation mechanism integrated with an aggregated signing technique to identify the untrusted aggregator and assure the data source and the identity of the sender. Security and performance evaluations are performed, including off-chain and on-chain experiments and simulations, to assess the security and efficiency of the scheme.

Suggested Citation

  • Hany Habbak & Mohamed Baza & Mohamed M. E. A. Mahmoud & Khaled Metwally & Ahmed Mattar & Gouda I. Salama, 2022. "Privacy-Preserving Charging Coordination Scheme for Smart Power Grids Using a Blockchain," Energies, MDPI, vol. 15(23), pages 1-23, November.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:23:p:8996-:d:986528
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    References listed on IDEAS

    as
    1. Liu, Lu & Zhou, Kaile, 2022. "Electric vehicle charging scheduling considering urgent demand under different charging modes," Energy, Elsevier, vol. 249(C).
    2. Kaile Zhou & Lulu Wen, 2022. "Electric Vehicle Charging Scheduling Considering Different Charging Demands," Springer Books, in: Smart Energy Management, chapter 0, pages 223-249, Springer.
    3. Baloglu, Ulas Baran & Demir, Yakup, 2018. "Lightweight privacy-preserving data aggregation scheme for smart grid metering infrastructure protection," International Journal of Critical Infrastructure Protection, Elsevier, vol. 22(C), pages 16-24.
    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. Hany Habbak & Mohamed Mahmoud & Mostafa M. Fouda & Maazen Alsabaan & Ahmed Mattar & Gouda I. Salama & Khaled Metwally, 2023. "Efficient One-Class False Data Detector Based on Deep SVDD for Smart Grids," Energies, MDPI, vol. 16(20), pages 1-28, October.
    2. Mostafa M. Fouda & Mohamed I. Ibrahem, 2023. "Secure and Efficient Communication in Smart Grids," Energies, MDPI, vol. 16(15), pages 1-2, July.
    3. Xiangyang Yu & Xiaojing Wang, 2023. "Research on Carbon-Trading Model of Urban Public Transport Based on Blockchain Technology," Energies, MDPI, vol. 16(6), pages 1-21, March.
    4. Hany Habbak & Mohamed Mahmoud & Khaled Metwally & Mostafa M. Fouda & Mohamed I. Ibrahem, 2023. "Load Forecasting Techniques and Their Applications in Smart Grids," Energies, MDPI, vol. 16(3), pages 1-33, February.

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