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1.清华大学五道口金融学院,北京市 100084
2.清华大学交叉信息研究院,北京市 100084
3.华控清交信息科技(北京)有限公司,北京市 100084
Received:31 October 2022,
Revised:2023-05-12,
Published Online:01 August 2023,
Published:10 October 2023
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FAN Hang,XU Wei,FAN Xiaoyu,et al.Application Analysis and Prospect of Privacy-preserving Computation in New Power System[J].Automation of Electric Power Systems,2023,47(19):187-199.
凡航,徐葳,范晓昱等.隐私计算在新型电力系统中的应用分析与展望[J].电力系统自动化,2023,47(19):187-199. DOI: 10.7500/AEPS20221031007.
FAN Hang,XU Wei,FAN Xiaoyu,et al.Application Analysis and Prospect of Privacy-preserving Computation in New Power System[J].Automation of Electric Power Systems,2023,47(19):187-199. DOI: 10.7500/AEPS20221031007.
新型电力系统是一个以新能源为主体的典型信息-物理-社会融合系统,利用跨主体的数据进行联合智能计算和智能调控,对于保障电力系统的安全稳定运行具有重要意义。随着国家数据资产化和数据安全相关法案的出台,在包含多主体的市场中保护数据隐私、避免数据直接共享逐渐得到广泛关注。较多的研究者开始探讨使用隐私计算方法在保护原始数据的同时实现数据挖掘和分析。但隐私计算技术种类丰富、安全假设多样,需要根据具体应用场景和需求特性(如安全要求、性能要求、准确度要求等)有针对性地设计隐私计算方案。文中对隐私计算的基本概念进行了阐述,并对该技术目前在新型电力系统中的多个应用场景进行了分析和总结。最后,讨论了当前应用中存在的问题和不足,给出了未来在新型电力系统中实现隐私计算应用的相关建议。相关思考有望为电网领域隐私计算的研究和应用提供参考,并最终促进能源领域数据的安全、高效流通。
The new power system is a typical cyber-physical-social integrated system with renewable energy as the main body. It is of great significance to use cross-subject data for joint intelligent computing and intelligent regulation to ensure the safe and stable operation of the power system. With the introduction of related laws on national data assetization and data security
preserving data privacy and avoiding direct data sharing in markets including multiple antities has gradually received widespread attention. More and more researchers begin to explore the use of privacy-preserving computation methods to achieve data mining and analysis while protecting the original data. However
there are various types of privacy-preserving computation technologies and diverse security assumptions
which require targeted design of privacy computing solutions based on specific application scenarios and demand characteristics
such as security requirements
performance requirements
and accuracy requirements. The basic concepts of privacy computing are expounded and multiple application scenarios of this technology in new power systems are analyzed and summarized. Privacy-preserving computation technology is a cutting-edge technology involving cryptography
computer science
and network science. Finally
the problems and shortcomings in current applications are discussed
and relevant suggestions for implementing privacy computing applications in new power systems in the future are given. It is expected that the relevant thoughts can provide a reference for the research and application of privacy computing in the power grid field
and ultimately promote the safe and efficient circulation of data in the energy industry.
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