分布式能源2026，Vol.11Issue(4)：15-28,14.DOI:10.16513/j.2096-2185.DE.25100530
虚拟电厂联邦学习与可信执行环境应用综述
Application Review of Federated Learning and Trusted Execution Environment in Virtual Power Plants
摘要
Abstract
The efficient operation of virtual power plants(VPPs)relies on massive heterogeneous data interactions,facing the fundamental contradiction between data value mining and privacy protection.Addressing the challenges of data silos,single points of failure,and privacy leakage in centralized management,this paper reviews the application status and integration solutions of federated learning and trusted execution environment in VPPs.Through comparative analysis of blockchain and cryptographic collaboration schemes,the advantages of federated learning in privacy protection,collaboration efficiency,and technical adaptability are clarified.The applications of federated learning in VPP load forecasting,distributed energy resource coordination,electricity market trading,and demand response are systematically reviewed,along with an analysis of trusted execution environment mechanisms that ensure computational confidentiality and integrity through hardware isolation.The integration architecture of both technologies is emphasized:trusted execution environment addresses federated learning's vulnerabilities in parameter leakage and poisoning attack defense by protecting model aggregation processes and sensitive data processing,while federated learning's distributed characteristics overcome the performance and scalability bottlenecks of trusted hardware.This integrated technology enables"data availability without visibility",and provides a feasible path for secure and efficient data collaboration in the energy internet.On the basis,this paper further discusses future challenges related to performance optimization,side-channel defense,and standardization.关键词
虚拟电厂(VPP)/联邦学习/可信执行环境/数据安全/隐私保护Key words
virtual power plant(VPP)/federated learning/trusted execution environment/data security/privacy protection分类
能源科技引用本文复制引用
李江南,欧鸣宇,蒋季儒,谭俊丰,黄宇翔,陈皓勇..虚拟电厂联邦学习与可信执行环境应用综述[J].分布式能源,2026,11(4):15-28,14.基金项目
中国南方电网有限责任公司重点科技项目(090000KC23090025) This work is supported by the Key Science and Technology Project of China Southern Power Grid Co.,Ltd.(No.090000KC23090025). （090000KC23090025）
