摘要
传统电力系统与其他能源系统不断交叉融合,逐渐形成能源互联的新生态。在能源互联网中,数据使用权与数据所有权分离、信息资源与计算资源分离的特征使得多主体协同优化的隐私保护问题日益突出。文中从能源互联网协同优化的典型模式出发,总结了传统第三方代理计算模式及无第三方交互计算模式的隐私安全风险,提出了考虑隐私保护的能源互联网协同优化初步技术方案。首先,面向含第三方场景提出了基于信息伪装机制的安全代理计算方案,并研究了该方案的算法特性、算子构造方法以及基于云服务的用户侧、集群级、系统级应用场景。然后,面向无第三方场景提出了基于秘密分享原理的安全多方交互计算方案,并结合多中心化和全分布式两种应用架构,分析了该方案应用于海量主体或少量主体场景时的特性差异。最后,所述方案从数据隐私性和计算安全性层面,保障数据所有者的权益,遏制并降低能源互联网协同优化计算的数据泄露风险,实现可靠隐私保护。
The accelerated integration of traditional power systems with other energy systems leads to a new ecology of energy interconnection.In the Energy Internet,the separation of data usage rights and data ownership,and the separation of information resources and computation resources make the privacy preservation problem of multi-party collaborative optimization increasingly prominent.Starting from the analysis of typical modes for collaborative optimization of Energy Internet,this paper summarizes the privacy risks of the traditional agent computation mode with a third party,and interactive computation mode without any third party.Preliminary technical schemes for mechanism collaborative optimization of Energy Internet considering privacy preservation are proposed.First,a secure agent computation scheme based on information masking is proposed for the scenarios with a third party.In this scheme,the characteristics of information masking algorithms,the construction method for operators and its application scenarios at the user level,cluster level and system level based on cloud services are studied.Then,a secure multiparty interactive computation scheme based on secret sharing principle is proposed for the scenarios without any third party.Combined with the multi-centric and fully distributed application architectures,the differences in characteristics of this scheme when applied to the scenarios with a large number of clients or a small number of clients are analyzed.The proposed schemes protect the rights and interests of data owners from the perspective of data privacy and computation security,reduce the risk of data disclosure in collaborative optimization computation of Energy Internet,and finally achieve reliable privacy preservation.
作者
郭庆来
田年丰
孙宏斌
GUO Qinglai;TIAN Nianfeng;SUN Hongbin(Department of Electrical Engineering,Tsinghua University,Beijing 100084,China;State Key Laboratory of Control and Simulation of Power Systems and Generation Equipments(Tsinghua University),Beijing 100084,China)
出处
《电力系统自动化》
EI
CSCD
北大核心
2023年第8期2-14,共13页
Automation of Electric Power Systems
基金
国家电网有限公司科技项目(52094022001K)。
关键词
能源互联网
协同优化
隐私保护
安全多方计算
信息伪装
秘密分享
Energy Internet
collaborative optimization
privacy preservation
secure multi-party computation
information masking
secret sharing
