IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v402y2025ipas0306261925015612.html

3STD-SES: Secure sharing scheme of trusted data of shared energy storage towards renewable energy accommodation scenario in a blockchain environment

Author

Listed:
  • Qiu, Weiqiang
  • Lin, Zhenzhi
  • Zhang, Tianhan
  • Chen, Changming
  • Li, Yongbin
  • Zhang, Zhi
  • Ma, Yuanqian
  • Yang, Li

Abstract

With the increase of the renewable energy installed capacity, shared energy storage (SES) has played an important role in the renewable energy accommodation scenario. Decision-makers need to analyze renewable energy accommodation capacity of SES using user data, but privacy concerns prevent data sharing, and authenticity risks exist. Given this background, a Secure Sharing Scheme of Trusted Data of SES (i.e., 3STD-SES), which combines with blockchain and a fully homomorphic encryption scheme, is proposed for guaranteeing data privacy and data authenticity in the statistical process of the accommodated renewable energy. Firstly, an SES operation framework based on power blockchain is presented, and on this basis, the generation, storage and sharing mechanisms of trusted data of SES are designed, which create a traceable and verifiable trust chain for the shared data. Secondly, a homomorphic encryption-based scheme counts accommodated energy without exposing raw data, which can fully preserve the privacy of SES users. Finally, the actual data from an SES trading pilot project in Qinghai, China, is taken as an example to verify the feasibility and applicability of the proposed scheme. The results show that 3STD-SES can enable decision makers to obtain the authentic, accurate and integral accommodated renewable energy with the privacy protection of SES users, and meet security requirements in the field of data sharing for the SES business model.

Suggested Citation

  • Qiu, Weiqiang & Lin, Zhenzhi & Zhang, Tianhan & Chen, Changming & Li, Yongbin & Zhang, Zhi & Ma, Yuanqian & Yang, Li, 2025. "3STD-SES: Secure sharing scheme of trusted data of shared energy storage towards renewable energy accommodation scenario in a blockchain environment," Applied Energy, Elsevier, vol. 402(PA).
  • Handle: RePEc:eee:appene:v:402:y:2025:i:pa:s0306261925015612
    DOI: 10.1016/j.apenergy.2025.126831
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261925015612
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.apenergy.2025.126831?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    as
    1. Lombardi, P. & Schwabe, F., 2017. "Sharing economy as a new business model for energy storage systems," Applied Energy, Elsevier, vol. 188(C), pages 485-496.
    2. Han, Dong & Zhang, Chengzhenghao & Ping, Jian & Yan, Zheng, 2020. "Smart contract architecture for decentralized energy trading and management based on blockchains," Energy, Elsevier, vol. 199(C).
    3. Chang, Hsiu-Chuan & Ghaddar, Bissan & Nathwani, Jatin, 2022. "Shared community energy storage allocation and optimization," Applied Energy, Elsevier, vol. 318(C).
    4. He, Xian & Delarue, Erik & D'haeseleer, William & Glachant, Jean-Michel, 2011. "A novel business model for aggregating the values of electricity storage," Energy Policy, Elsevier, vol. 39(3), pages 1575-1585, March.
    5. Michael R. Galbreth & Bikram Ghosh & Mikhael Shor, 2012. "Social Sharing of Information Goods: Implications for Pricing and Profits," Marketing Science, INFORMS, vol. 31(4), pages 603-620, July.
    6. Martin Albrecht & Melissa Chase & Hao Chen & Jintai Ding & Shafi Goldwasser & Sergey Gorbunov & Shai Halevi & Jeffrey Hoffstein & Kim Laine & Kristin Lauter & Satya Lokam & Daniele Micciancio & Dustin, 2021. "Homomorphic Encryption Standard," Springer Books, in: Kristin Lauter & Wei Dai & Kim Laine (ed.), Protecting Privacy through Homomorphic Encryption, pages 31-62, Springer.
    7. Han, Xiaojuan & Li, Jiarong & Zhang, Zhewen, 2023. "Dynamic game optimization control for shared energy storage in multiple application scenarios considering energy storage economy," Applied Energy, Elsevier, vol. 350(C).
    8. Liu, Wei-Jen & Chiu, Wei-Yu & Hua, Weiqi, 2024. "Blockchain-enabled renewable energy certificate trading: A secure and privacy-preserving approach," Energy, Elsevier, vol. 290(C).
    9. Babaei, Ardavan & Babaee Tirkolaee, Erfan & Ali, Sadia Samar, 2025. "Assessing the viability of blockchain technology in renewable energy supply chains: A consolidation framework," Renewable and Sustainable Energy Reviews, Elsevier, vol. 212(C).
    10. Walker, Awnalisa & Kwon, Soongeol, 2021. "Design of structured control policy for shared energy storage in residential community: A stochastic optimization approach," Applied Energy, Elsevier, vol. 298(C).
    11. Zhou, Kaile & Fu, Chao & Yang, Shanlin, 2016. "Big data driven smart energy management: From big data to big insights," Renewable and Sustainable Energy Reviews, Elsevier, vol. 56(C), pages 215-225.
    Full references (including those not matched with items on IDEAS)

    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. Talihati, Baligen & Tao, Shengyu & Fu, Shiyi & Zhang, Bowen & Fan, Hongtao & Li, Qifen & Lv, Xiaodong & Sun, Yaojie & Wang, Yu, 2024. "Energy storage sharing in residential communities with controllable loads for enhanced operational efficiency and profitability," Applied Energy, Elsevier, vol. 373(C).
    2. Weiqiang Qiu & Sheng Zhou & Yang Yang & Xiaoying Lv & Ting Lv & Yuge Chen & Ying Huang & Kunming Zhang & Hongfei Yu & Yunchu Wang & Yuanqian Ma & Zhenzhi Lin, 2023. "Application Prospect, Development Status and Key Technologies of Shared Energy Storage toward Renewable Energy Accommodation Scenario in the Context of China," Energies, MDPI, vol. 16(2), pages 1-21, January.
    3. Zhaonian Ye & Yongzhen Wang & Kai Han & Changlu Zhao & Juntao Han & Yilin Zhu, 2023. "Bi-Objective Optimization and Emergy Analysis of Multi-Distributed Energy System Considering Shared Energy Storage," Sustainability, MDPI, vol. 15(2), pages 1-23, January.
    4. Zhang, Ziyu & Ding, Tao & Zhou, Quan & Sun, Yuge & Qu, Ming & Zeng, Ziyu & Ju, Yuntao & Li, Li & Wang, Kang & Chi, Fangde, 2021. "A review of technologies and applications on versatile energy storage systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 148(C).
    5. Müller, Simon C. & Welpe, Isabell M., 2018. "Sharing electricity storage at the community level: An empirical analysis of potential business models and barriers," Energy Policy, Elsevier, vol. 118(C), pages 492-503.
    6. Fina, Bernadette & Ribo-Perez, David, 2025. "Economic incentive fundamentals for the operation of energy communities with different storage concepts," Energy Economics, Elsevier, vol. 151(C).
    7. Xie, Yulong & Li, Lee & Hou, Tianyu & Luo, Kang & Xu, Zhenyu & Dai, Mingcheng & Zhang, Lixiong, 2024. "Shared energy storage configuration in distribution networks: A multi-agent tri-level programming approach," Applied Energy, Elsevier, vol. 372(C).
    8. Jiahao Chen & Bing Sun & Yuan Zeng & Ruipeng Jing & Shimeng Dong & Jingran Wang, 2023. "An Optimal Scheduling Method of Shared Energy Storage System Considering Distribution Network Operation Risk," Energies, MDPI, vol. 16(5), pages 1-24, March.
    9. Arteaga, Juan & Zareipour, Hamidreza & Amjady, Nima, 2021. "Energy Storage as a Service: Optimal sizing for Transmission Congestion Relief," Applied Energy, Elsevier, vol. 298(C).
    10. Scheller, Fabian & Burkhardt, Robert & Schwarzeit, Robert & McKenna, Russell & Bruckner, Thomas, 2020. "Competition between simultaneous demand-side flexibility options: the case of community electricity storage systems," Applied Energy, Elsevier, vol. 269(C).
    11. He, Ye & Wu, Hongbin & Wu, Andrew Y. & Li, Peng & Ding, Ming, 2024. "Optimized shared energy storage in a peer-to-peer energy trading market: Two-stage strategic model regards bargaining and evolutionary game theory," Renewable Energy, Elsevier, vol. 224(C).
    12. Fabian Scheller & Robert Burkhardt & Robert Schwarzeit & Russell McKenna & Thomas Bruckner, 2020. "Competition between simultaneous demand-side flexibility options: The case of community electricity storage systems," Papers 2011.05809, arXiv.org.
    13. Pedro Crespo Del Granado & Stein Wallace & Zhan Pang, 2016. "The impact of wind uncertainty on the strategic valuation of distributed electricity storage," Computational Management Science, Springer, vol. 13(1), pages 5-27, January.
    14. De Vivero-Serrano, Gustavo & Bruninx, Kenneth & Delarue, Erik, 2019. "Implications of bid structures on the offering strategies of merchant energy storage systems," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
    15. Miguel Ángel Rodríguez López & Diego Rodríguez Rodríguez, 2024. "La aplicación de datos masivos en economía de la energía: una revisión," Working Papers 2024-08, FEDEA.
    16. Zhou, Yuekuan & Lund, Peter D., 2023. "Peer-to-peer energy sharing and trading of renewable energy in smart communities ─ trading pricing models, decision-making and agent-based collaboration," Renewable Energy, Elsevier, vol. 207(C), pages 177-193.
    17. Cui, Shiting & Zhu, Ruijin & Wu, Jun, 2024. "A double layer energy cooperation framework for prosumer groups in high altitude areas," Renewable Energy, Elsevier, vol. 224(C).
    18. Tom Brijs & Daniel Huppmann & Sauleh Siddiqui & Ronnie Belmans, 2016. "Auction-Based Allocation of Shared Electricity Storage Resources through Physical Storage Rights," Discussion Papers of DIW Berlin 1566, DIW Berlin, German Institute for Economic Research.
    19. Félix González & Paul Arévalo & Luis Ramirez, 2025. "Game Theory and Robust Predictive Control for Peer-to-Peer Energy Management: A Pathway to a Low-Carbon Economy," Sustainability, MDPI, vol. 17(5), pages 1-23, February.
    20. Jihoon Moon & Junhong Kim & Pilsung Kang & Eenjun Hwang, 2020. "Solving the Cold-Start Problem in Short-Term Load Forecasting Using Tree-Based Methods," Energies, MDPI, vol. 13(4), pages 1-37, February.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:eee:appene:v:402:y:2025:i:pa:s0306261925015612. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    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.