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A Dynamic Incentive Mechanism for Smart Grid Data Sharing Based on Evolutionary Game Theory

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Listed:
  • Lihua Zhang

    (School of Software, East China Jiaotong University, Nanchang 330013, China)

  • Qingyu Lu

    (School of Software, East China Jiaotong University, Nanchang 330013, China)

  • Rui Huang

    (School of Electrical and Automation Engineering, East China Jiaotong University, Nanchang 330013, China)

  • Shihong Chen

    (School of Electrical and Automation Engineering, East China Jiaotong University, Nanchang 330013, China)

  • Qianqian Yang

    (School of Software, East China Jiaotong University, Nanchang 330013, China)

  • Jinguang Gu

    (College of Computer Science and Technology, Wuhan University of Science and Technology, Wuhan 430065, China)

Abstract

With the increasing popularization and application of the smart grid, the harm of the data silo issue in the smart grid is more and more prominent. Therefore, it is especially critical to promote data interoperability and sharing in the smart grid. Existing data-sharing schemes generally lack effective incentive mechanisms, and data holders are reluctant to share data due to privacy and security issues. Because of the above issues, a dynamic incentive mechanism for smart grid data sharing based on evolutionary game theory is proposed. Firstly, several basic assumptions about the evolutionary game model are given, and the evolutionary game payoff matrix is established. Then, we analyze the stabilization strategy of the evolutionary game based on the payoff matrix, and propose a dynamic incentive mechanism for smart grid data sharing based on evolutionary game theory according to the analysis results, aiming to encourage user participation in data sharing. We further write the above evolutionary game model into a smart contract that can be invoked by the two parties involved in data sharing. Finally, several factors affecting the sharing of data between two users are simulated, and the impact of different factors on the evolutionary stabilization strategy is discussed. The simulation results verify the positive or negative incentives of these parameters in the data-sharing game process, and several factors influencing the users’ data sharing are specifically analyzed. This dynamic incentive mechanism scheme for smart grid data sharing based on evolutionary game theory provides new insights into effective incentives for current smart grid data sharing.

Suggested Citation

  • Lihua Zhang & Qingyu Lu & Rui Huang & Shihong Chen & Qianqian Yang & Jinguang Gu, 2023. "A Dynamic Incentive Mechanism for Smart Grid Data Sharing Based on Evolutionary Game Theory," Energies, MDPI, vol. 16(24), pages 1-22, December.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:24:p:8125-:d:1302637
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    References listed on IDEAS

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    1. Tang, Rui & Wang, Shengwei & Li, Hangxin, 2019. "Game theory based interactive demand side management responding to dynamic pricing in price-based demand response of smart grids," Applied Energy, Elsevier, vol. 250(C), pages 118-130.
    2. Sleep, Stefan & Gala, Prachi & Harrison, Dana E., 2023. "Removing silos to enable data-driven decisions: The importance of marketing and IT knowledge, cooperation, and information quality," Journal of Business Research, Elsevier, vol. 156(C).
    3. Anuraag Bukkuri & Joel S. Brown, 2021. "Evolutionary Game Theory: Darwinian Dynamics and the G Function Approach," Games, MDPI, vol. 12(4), pages 1-19, September.
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    Cited by:

    1. Nan Jiang & Yiwen Ma, 2025. "Research on Incentive Mechanisms in the Data Market Based on a Multitask Principal–Agent Model," Sustainability, MDPI, vol. 17(4), pages 1-26, February.

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