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Decentralized blockchain-based consensus for Optimal Power Flow solutions

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  • Foti, Magda
  • Mavromatis, Costas
  • Vavalis, Manolis

Abstract

We design, implement and analyze a decentralized consensus algorithm based on the blockchain technology for the solution of the Optimal Power Flow problem. The proposed algorithm enables independent power grid nodes, without prior trust on each other, to reach an agreement on the Optimal Power Flow solution. We decompose the Optimal Power Flow problem using a blockchain-based Alternating Direction Method of Multipliers and we comment on efficiency, trust, security and transparency issues. The successive iterants of the solution of the power flow problem are securely stored on the blockchain, removing the need for a central operating authority, while allowing network nodes to verify the validity and optimality of the solution. We illustrate the effectiveness of the consensus algorithm presented through simulation experiments on the 39-bus New England transmission system, and IEEE-57 and IEEE-118 benchmark systems. We systematically compare the effectiveness of the proposed algorithm with well established blockchain consensus algorithms. The results show that our method maintains the convergence characteristics of the Alternating Direction Method of Multipliers iterative scheme and enables independent network nodes to reach consensus.

Suggested Citation

  • Foti, Magda & Mavromatis, Costas & Vavalis, Manolis, 2021. "Decentralized blockchain-based consensus for Optimal Power Flow solutions," Applied Energy, Elsevier, vol. 283(C).
  • Handle: RePEc:eee:appene:v:283:y:2021:i:c:s0306261920315221
    DOI: 10.1016/j.apenergy.2020.116100
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    Cited by:

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    2. Lu, Xin & Qiu, Jing & Zhang, Cuo & Lei, Gang & Zhu, Jianguo, 2024. "Seizing unconventional arbitrage opportunities in virtual power plants: A profitable and flexible recruitment approach," Applied Energy, Elsevier, vol. 358(C).
    3. Qinghan Sun & Huan Ma & Tian Zhao & Yonglin Xin & Qun Chen, 2024. "Break down the decentralization-security-privacy trilemma in management of distributed energy systems," Nature Communications, Nature, vol. 15(1), pages 1-12, December.
    4. Dong, Lianxin & Fan, Shuai & Wang, Zhihua & Xiao, Jucheng & Zhou, Huan & Li, Zuyi & He, Guangyu, 2021. "An adaptive decentralized economic dispatch method for virtual power plant," Applied Energy, Elsevier, vol. 300(C).
    5. 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).
    6. Uyikumhe Damisa & Nnamdi I. Nwulu & Pierluigi Siano, 2022. "Towards Blockchain-Based Energy Trading: A Smart Contract Implementation of Energy Double Auction and Spinning Reserve Trading," Energies, MDPI, vol. 15(11), pages 1-16, June.
    7. Uyikumhe Damisa & Nnamdi I. Nwulu, 2022. "Blockchain-Based Auctioning for Energy Storage Sharing in a Smart Community," Energies, MDPI, vol. 15(6), pages 1-12, March.
    8. Tanus Bikram Malla & Abhinav Bhattarai & Amrit Parajuli & Ashish Shrestha & Bhupendra Bimal Chhetri & Kamal Chapagain, 2022. "Status, Challenges and Future Directions of Blockchain Technology in Power System: A State of Art Review," Energies, MDPI, vol. 15(22), pages 1-26, November.
    9. Yang, Jun & Sun, Fengyuan & Wang, Haitao, 2023. "Distributed collaborative optimal economic dispatch of integrated energy system based on edge computing," Energy, Elsevier, vol. 284(C).
    10. Couraud, Benoit & Andoni, Merlinda & Robu, Valentin & Norbu, Sonam & Chen, Si & Flynn, David, 2023. "Responsive FLEXibility: A smart local energy system," Renewable and Sustainable Energy Reviews, Elsevier, vol. 182(C).

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