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arXiv 2602.23698cs.CR
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考虑网络费用的隐私保护本地能源交易

Privacy-Preserving Local Energy Trading Considering Network Fees

The University of Manchester(曼彻斯特大学);KU Leuven(荷语鲁汶大学)

Eman Alqahtani, Mustafa A. Mustafa

AI总结:

本文提出一种考虑网络费用的隐私保护本地能源交易协议,通过双拍卖机制和安全多方计算实现高效且安全的能源交易。

摘要:

随着分布式能源资源的广泛部署,本地能源市场(LEMs)已作为一种有前景的方法出现,旨在通过直接交易供能者和消费者来平衡间歇性发电和需求。然而,LEMs涉及处理敏感的参与者数据,如果得不到保护,将带来隐私风险。同时,由于电力是通过物理电力网络交换的,市场机制应考虑物理约束和与网络相关的成本。现有工作通常将这些问题分别处理,要么通过纳入电网相关方面,要么通过提供隐私保护。为解决这一差距,我们提出了一种考虑网络费用的隐私保护协议,该费用可以促使参与者尊重物理限制。该协议基于先前工作的双拍卖机制进行调整,以更高效地应用我们的隐私保护方法。为了保护参与者的数据,我们使用安全多方计算。此外,采用Schnorr的身份协议进行多方验证,以确保认证参与而不牺牲隐私。我们进一步优化协议以减少通信和轮次复杂性。我们证明该协议满足其安全要求,并通过实验展示其在典型LEMs规模下的可行性:一个有5000名参与者市场的清算可以在4.17分钟内完成。

英文摘要:

Driven by the widespread deployment of distributed energy resources, local energy markets (LEMs) have emerged as a promising approach for enabling direct trades among prosumers and consumers to balance intermittent generation and demand locally. However, LEMs involve processing sensitive participant data, which, if not protected, poses privacy risks. At the same time, since electricity is exchanged over the physical power network, market mechanisms should consider physical constraints and network-related costs. Existing work typically addresses these issues separately, either by incorporating grid-related aspects or by providing privacy protection. To address this gap, we propose a privacy-preserving protocol for LEMs, with consideration of network fees that can incite participants to respect physical limits. The protocol is based on a double-auction mechanism adapted from prior work to enable more efficient application of our privacy-preserving approach. To protect participants' data, we use secure multiparty computation. In addition, Schnorr's identification protocol is employed with multiparty verification to ensure authenticated participation without compromising privacy. We further optimise the protocol to reduce communication and round complexity. We prove that the protocol meets its security requirements and show through experimentation its feasibility at a typical LEM scale: a market with 5,000 participants can be cleared in 4.17 minutes.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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