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Peer-to-peer energy trading in a microgrid leveraged by smart contracts

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  • Vieira, Guilherme
  • Zhang, Jie

Abstract

The current electricity networks were not initially designed for the high integration of variable generation technologies. They suffer significant losses due to the combustion of fossil fuels, the long-distance transmission, and distribution of the power to the network. Recently, prosumers, both consumers and producers, emerge with the increasing affordability to invest in domestic solar systems. Prosumers may trade within their communities to better manage their demand and supply as well as providing social and economic benefits. In this paper, we explore the use of Blockchain technologies and auction mechanisms to facilitate autonomous peer-to-peer energy trading within microgrids. We design two frameworks that utilize the smart contract functionality in Ethereum and employ the continuous double auction and uniform-price double-sided auction mechanisms, respectively. We validate our design by conducting A/B tests to compare the performance of different frameworks on a real-world dataset. The key characteristics of the two frameworks and several cost analyses are presented for comparison. Our results demonstrate that a P2P trading platform that integrates the blockchain technologies and agent-based systems is promising to complement the current centralized energy grid. We also identify a number of limitations, alternative solutions, and directions for future work.

Suggested Citation

  • Vieira, Guilherme & Zhang, Jie, 2021. "Peer-to-peer energy trading in a microgrid leveraged by smart contracts," Renewable and Sustainable Energy Reviews, Elsevier, vol. 143(C).
    • Handle: RePEc:eee:rensus:v:143:y:2021:i:c:s1364032121001945
    DOI: 10.1016/j.rser.2021.110900
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    References listed on IDEAS

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    1. Mengelkamp, Esther & Gärttner, Johannes & Rock, Kerstin & Kessler, Scott & Orsini, Lawrence & Weinhardt, Christof, 2018. "Designing microgrid energy markets," Applied Energy, Elsevier, vol. 210(C), pages 870-880.
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    3. Gode, Dhananjay K & Sunder, Shyam, 1993. "Allocative Efficiency of Markets with Zero-Intelligence Traders: Market as a Partial Substitute for Individual Rationality," Journal of Political Economy, University of Chicago Press, vol. 101(1), pages 119-137, February.
    4. Mariam, Lubna & Basu, Malabika & Conlon, Michael F., 2016. "Microgrid: Architecture, policy and future trends," Renewable and Sustainable Energy Reviews, Elsevier, vol. 64(C), pages 477-489.
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    Cited by:

    1. Umar, Abdullah & Kumar, Deepak & Ghose, Tirthadip, 2022. "Blockchain-based decentralized energy intra-trading with battery storage flexibility in a community microgrid system," Applied Energy, Elsevier, vol. 322(C).
    2. Zeng, Yu & Wei, Xuan & Yao, Yuan & Xu, Yinliang & Sun, Hongbin & Kin Victor Chan, Wai & Feng, Wei, 2023. "Determining the pricing and deployment strategy for virtual power plants of peer-to-peer prosumers: A game-theoretic approach," Applied Energy, Elsevier, vol. 345(C).
    3. 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.
    4. Yu, Vincent F. & Le, Thi Huynh Anh & Gupta, Jatinder N.D., 2022. "Sustainable microgrid design with multiple demand areas and peer-to-peer energy trading involving seasonal factors and uncertainties," Renewable and Sustainable Energy Reviews, Elsevier, vol. 161(C).
    5. Wu, Ying & Wu, Yanpeng & Cimen, Halil & Vasquez, Juan C. & Guerrero, Josep M., 2022. "Towards collective energy Community: Potential roles of microgrid and blockchain to go beyond P2P energy trading," Applied Energy, Elsevier, vol. 314(C).
    6. Andrzej Jezierski & Cezary Mańkowski & Rafał Śpiewak, 2021. "Energy Savings Analysis in Logistics of a Wind Farm Repowering Process: A Case Study," Energies, MDPI, vol. 14(17), pages 1-23, September.
    7. Sarah O’Connell & Marcus Martin Keane, 2021. "Development of a Framework for Activation of Aggregator Led Flexibility," Energies, MDPI, vol. 14(16), pages 1-15, August.
    8. Botelho, D.F. & de Oliveira, L.W. & Dias, B.H. & Soares, T.A. & Moraes, C.A., 2022. "Integrated prosumers–DSO approach applied in peer-to-peer energy and reserve tradings considering network constraints," Applied Energy, Elsevier, vol. 317(C).
    9. Minuto, Francesco Demetrio & Lanzini, Andrea, 2022. "Energy-sharing mechanisms for energy community members under different asset ownership schemes and user demand profiles," Renewable and Sustainable Energy Reviews, Elsevier, vol. 168(C).
    10. 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).
    11. Hahnel, Ulf J.J. & Fell, Michael J., 2022. "Pricing decisions in peer-to-peer and prosumer-centred electricity markets: Experimental analysis in Germany and the United Kingdom," Renewable and Sustainable Energy Reviews, Elsevier, vol. 162(C).
    12. Yap, Kah Yung & Chin, Hon Huin & Klemeš, Jiří Jaromír, 2023. "Blockchain technology for distributed generation: A review of current development, challenges and future prospect," Renewable and Sustainable Energy Reviews, Elsevier, vol. 175(C).
    13. Liu, Wei & Chau, K.T. & Tian, Xiaoyang & Wang, Hui & Hua, Zhichao, 2023. "Smart wireless power transfer — opportunities and challenges," Renewable and Sustainable Energy Reviews, Elsevier, vol. 180(C).
    14. Manuel Casquiço & Bruno Mataloto & Joao C. Ferreira & Vitor Monteiro & Joao L. Afonso & Jose A. Afonso, 2021. "Blockchain and Internet of Things for Electrical Energy Decentralization: A Review and System Architecture," Energies, MDPI, vol. 14(23), pages 1-26, December.

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