Decentralized Optimal Power Flow for Multi-Agent Active Distribution Networks: A Differentially Private Consensus ADMM Algorithm

IF 8.6 1区工程技术 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC

IEEE Transactions on Smart Grid Pub Date : 2024-08-29 DOI:10.1109/TSG.2024.3451793

Chao Lei;Siqi Bu;Qifan Chen;Qianggang Wang;Qin Wang;Dipti Srinivasan

引用次数: 0

Abstract

In multi-agent active distribution networks, the information exchanges in the ADMM algorithm for the decentralized distribution-level optimal power flow (D-OPF) may expose sensitive load flows of tie-lines across adjacent agents. This may be overheard by adversarial agents for business competition. To preserve this privacy, this paper proposes a differentially private consensus ADMM (DP-C-ADMM) algorithm, which can offer a mixture solution of both realistically optimal generator outputs and obfuscated-but-feasible load flows of tie-lines. And

$\epsilon -$

differential privacy holds for load flows of tie-lines across agents over iterations. Case study justifies the theoretical properties of this algorithm up to specified privacy parameters.

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多代理主动配电网络的分散式最佳功率流：一种差分私有共识 ADMM 算法

在多代理主动配电网络中，分散式配电级最佳功率流 (D-OPF) 的 ADMM 算法中的信息交换可能会暴露相邻代理之间连接线的敏感负荷流。这可能会被商业竞争中的敌对代理偷听到。为了保护这种隐私，本文提出了一种差异化私有共识 ADMM（DP-C-ADMM）算法，它可以提供现实最优发电机输出和模糊但可行的领带线负载流的混合解。在迭代过程中，各代理之间的领带线负载流的$epsilon -$差分隐私性是成立的。案例研究证明了该算法在指定隐私参数范围内的理论特性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

IEEE Transactions on Smart Grid ENGINEERING, ELECTRICAL & ELECTRONIC-

CiteScore

22.10

自引率

9.40%

发文量

526

审稿时长

6 months

期刊介绍： The IEEE Transactions on Smart Grid is a multidisciplinary journal that focuses on research and development in the field of smart grid technology. It covers various aspects of the smart grid, including energy networks, prosumers (consumers who also produce energy), electric transportation, distributed energy resources, and communications. The journal also addresses the integration of microgrids and active distribution networks with transmission systems. It publishes original research on smart grid theories and principles, including technologies and systems for demand response, Advance Metering Infrastructure, cyber-physical systems, multi-energy systems, transactive energy, data analytics, and electric vehicle integration. Additionally, the journal considers surveys of existing work on the smart grid that propose new perspectives on the history and future of intelligent and active grids.