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Consumer-centric decarbonization framework using Stackelberg game and Blockchain

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  • Hua, Weiqi
  • Jiang, Jing
  • Sun, Hongjian
  • Teng, Fei
  • Strbac, Goran

Abstract

Energy policy is too often not designed for energy consumers in a low-cost and consumer-friendly manner. This paper proposes a novel Stackelberg game and Blockchain-based framework that enables consumer-centric decarbonization by automating iterative negotiations between policy makers and consumers or generators to reduce carbon emissions. This iterative negotiation is modeled as a Stackelberg game-theoretic problem, and securely facilitated by Blockchain technologies. The policy maker formulates carbon prices and monetary compensation rates to dynamically incentivize the carbon reduction, whereas consumers and generators schedule their power profiles to minimize bills and maximize profits of generation, respectively. The negotiating agreement is yielded by reaching a Stackelberg equilibrium. The exchanged information and controlling functions are realized by using smart contracts of Blockchain technologies. Case studies of GB power systems show that the proposed framework can incentivize 9% more bill savings for consumers and 45.13% more energy generation from renewable energy sources. As a consumer-centric decarbonization framework, it can at least reduce carbon emissions by 40%.

Suggested Citation

  • Hua, Weiqi & Jiang, Jing & Sun, Hongjian & Teng, Fei & Strbac, Goran, 2022. "Consumer-centric decarbonization framework using Stackelberg game and Blockchain," Applied Energy, Elsevier, vol. 309(C).
  • Handle: RePEc:eee:appene:v:309:y:2022:i:c:s0306261921016226
    DOI: 10.1016/j.apenergy.2021.118384
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    Cited by:

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    2. Łukasz Jarosław Kozar & Adam Sulich, 2023. "Green Jobs in the Energy Sector," Energies, MDPI, vol. 16(7), pages 1-20, March.
    3. Arsenii Vilkov & Gang Tian, 2023. "Blockchain’s Scope and Purpose in Carbon Markets: A Systematic Literature Review," Sustainability, MDPI, vol. 15(11), pages 1-27, May.
    4. Yong Cui & Anselme Andriamahery & Lie Ao & Jian Zheng & Zhiqiang Huo, 2022. "Analysis of Optimal Operation of Multi-Energy Alliance Based on Multi-Scale Dynamic Cost Equilibrium Allocation," Sustainability, MDPI, vol. 14(24), pages 1-19, December.
    5. Liangjiang Wei & Wei Jian & Baochuan Fu & Baoping Jiang, 2023. "Research on Real-Time Trading Mechanism of Photovoltaic Microgrid Based on the Consortium Blockchain," Energies, MDPI, vol. 16(23), pages 1-14, November.
    6. Li, Junkai & Ge, Shaoyun & Xu, Zhengyang & Liu, Hong & Li, Jifeng & Wang, Chengshan & Cheng, Xueying, 2023. "A network-secure peer-to-peer trading framework for electricity-carbon integrated market among local prosumers," Applied Energy, Elsevier, vol. 335(C).
    7. Zhang, Bidan & Du, Yang & Chen, Xiaoyang & Lim, Eng Gee & Jiang, Lin & Yan, Ke, 2022. "A novel adaptive penalty mechanism for Peer-to-Peer energy trading," Applied Energy, Elsevier, vol. 327(C).

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