【摘要】 虚假数据注入攻击(false data injection attack, FDIA)是现代配电系统状态估计面临的主要网络攻击模式之一。为防御针对电力隐私数据安全的虚假数据注入攻击，提出了一种面向三相不平衡配电系统状态估计的分布式数据驱动FDIA检测模型和求解算法。结合配电系统不良数据检测原理，考虑节点电气隐私数据和专业攻击者的攻击偏好，提出了一种面向三相不平衡配电系统状态估计的多项式伪测量虚假数据注入攻击模式，通过基于变惩罚系数改进的交替方向乘子法(ρ-alternating direction method of multipliers,ρ-ADMM)进行分布式求解，保护数据隐私的同时实现高效准确地FDIA检测和篡改数据修正。通过在IEEE 123节点测试系统中设定不同攻击强度，分别与集中式方法和传统FDIA检测方法进行对比分析，验证了所提分布式检测算法的有效性。更多还原

【Abstract】 False data injection attack(FDIA) is one of the major cyber-attack patterns facing the state estimation of modern power distribution systems. To defend against false data injection attacks targeting power privacy data security,this paper proposes a distributed data-driven FDIA detection model and solution algorithm for three-phase unbalanced power distribution systems. A polynomial pseudo measurement false data attack pattern for state estimation of three-phase unbalanced distribution systems is discovered by combining the principle of bad data detection and considering the node power privacy data and the attacker’s preference. The distributed solution is performed by the variable penalty coefficient improved alternating direction method of multiplier(ρ-ADMM) method, which protects the data privacy while realizing efficient and accurate FDIA detection and tampered data correction. The effectiveness of the proposed distributed detection algorithm is verified by setting different attack strengths in the IEEE 123-node test system and comparing the analysis with the centralized method and the traditional FDIA detection method, respectively.更多还原