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<p>Peer-to-peer (P2P) energy trading represents a viable solution for the transition toward carbon-free energy systems, as they enable prosumers to exchange electricity at lower costs without the need for intermediaries. However, P2P networks require an infrastructure that supports the secure exchange and storage of information. In addition, a key challenge in P2P markets is ensuring economic balance among all network participants. This paper develops an integrated methodology for P2P energy trading by combining distributed optimization with <i>Blockchain</i> technology. To mitigate the challenges of economic balancing and data privacy, we implement an asynchronous distributed algorithm based on Replicator Dynamics within the Ethereum ecosystem. The proposed two-layer architecture utilizes smart contracts to facilitate optimal dispatch among prosumers while maintaining information immutability and security. Experimental implementation shows that the system achieves fast convergence in the optimization process without compromising agent privacy. The study concludes with an automated P2P market framework, demonstrating the potential of <i>Blockchain</i> as a robust infrastructure for decentralized energy management and distributed optimization.</p>

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Integrating distributed optimization algorithms into blockchain for P2P energy trading

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年2月17日

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  • Edinson Benavides,
  • Germán Obando,
  • Andrés Pantoja

摘要

Peer-to-peer (P2P) energy trading represents a viable solution for the transition toward carbon-free energy systems, as they enable prosumers to exchange electricity at lower costs without the need for intermediaries. However, P2P networks require an infrastructure that supports the secure exchange and storage of information. In addition, a key challenge in P2P markets is ensuring economic balance among all network participants. This paper develops an integrated methodology for P2P energy trading by combining distributed optimization with Blockchain technology. To mitigate the challenges of economic balancing and data privacy, we implement an asynchronous distributed algorithm based on Replicator Dynamics within the Ethereum ecosystem. The proposed two-layer architecture utilizes smart contracts to facilitate optimal dispatch among prosumers while maintaining information immutability and security. Experimental implementation shows that the system achieves fast convergence in the optimization process without compromising agent privacy. The study concludes with an automated P2P market framework, demonstrating the potential of Blockchain as a robust infrastructure for decentralized energy management and distributed optimization.