摘要
针对电力负荷预测中智能电表的数据获取,同时考虑到电表数据传输带来的隐私泄露问题,本文基于噪声添加机制和平均一致性理论研究智能电表数据的安全聚合。首先,基于智能电表的地理位置和电力系统架构,构建包括底层网络和上层网络的层次型通信拓扑,并为底层网络动态分配中继节点;其次,设计了级联一致性数据聚合算法,实现了底层网络和上层网络的级联聚合;再次,提出了一种隐私保护的噪声添加机制,在迭代过程中引入零和噪声,并证明其隐私保护度的收敛性;最后,通过数值仿真实验验证了所提考虑数据隐私的智能电表数据聚合方法的有效性。
In the context of data acquisition from smart meters for power load forecasting,while considering the privacy leakage issues caused by data transmission,this paper investigates the secure data aggregation for smart meters based on a noise addition mechanism and average consensus theory.First,a hierarchical communication topology was constructed,including both lower and upper networks,based on the geographical location of the smart meters and the power system architecture,with dynamic relay node allocation for the lower network.Second,a cascaded consensus data aggregation algorithm was designed,achieving cascaded aggregation across the lower and upper networks.Third,a privacy-protecting noise addition mechanism was proposed,introducing zero-sum noise during the iterative process,and the convergence of its privacy protection level was proven.Finally,some numerical simulations verified the effectiveness of the proposed privacy-protecting data aggregation method for smart meters.
作者
何平
蔡玥
顾杨青
李荷婷
胡伏原
HE Ping;CAI Yue;GU Yangqing;LI Heting;HU Fuyuan(State Grid Jiangsu Electric Power Co.Ltd.,Suzhou Power Supply Branch,Suzhou 215004,China;School of Electronic&Information Engineering,SUST,Suzhou 215009,China)
出处
《苏州科技大学学报(自然科学版)》
2025年第2期68-75,共8页
Journal of Suzhou University of Science and Technology(Natural Science Edition)
基金
国家自然科学基金项目(62476189)。
关键词
智能电表数据聚合
平均一致性
隐私保护
分层拓扑
data gathering for smart meter
average consensus
privacy protection
hierarchical communication topology
