IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v15y2022i23p8996-d986528.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/15/23/8996/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/15/23/8996/
    Download Restriction: no
    ---><---

    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. 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.
    3. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Hussain, Shahid & Irshad, Reyazur Rashid & Pallonetto, Fabiano & Hussain, Ihtisham & Hussain, Zakir & Tahir, Muhammad & Abimannan, Satheesh & Shukla, Saurabh & Yousif, Adil & Kim, Yun-Su & El-Sayed, H, 2023. "Hybrid coordination scheme based on fuzzy inference mechanism for residential charging of electric vehicles," Applied Energy, Elsevier, vol. 352(C).
    2. Liu, Shuohan & Cao, Yue & Ni, Qiang & Xu, Lexi & Zhu, Yongdong & Zhang, Xin, 2023. "Towards reservation-based E-mobility service via hybrid of V2V and G2V charging modes," Energy, Elsevier, vol. 268(C).
    3. Pegah Alaee & Julius Bems & Amjad Anvari-Moghaddam, 2023. "A Review of the Latest Trends in Technical and Economic Aspects of EV Charging Management," Energies, MDPI, vol. 16(9), pages 1-28, April.
    4. Zhao, Zhonghao & Lee, Carman K.M. & Ren, Jingzheng, 2024. "A two-level charging scheduling method for public electric vehicle charging stations considering heterogeneous demand and nonlinear charging profile," Applied Energy, Elsevier, vol. 355(C).
    5. Tostado-Véliz, Marcos & Jordehi, Ahmad Rezaee & Mansouri, Seyed Amir & Jurado, Francisco, 2023. "A two-stage IGDT-stochastic model for optimal scheduling of energy communities with intelligent parking lots," Energy, Elsevier, vol. 263(PD).
    6. Zeinab Teimoori & Abdulsalam Yassine, 2022. "A Review on Intelligent Energy Management Systems for Future Electric Vehicle Transportation," Sustainability, MDPI, vol. 14(21), pages 1-23, October.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:15:y:2022:i:23:p:8996-:d:986528. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.