This article is centered on the cybersecurity research of dynamic state estimation for power systems with measurement delays. Relying on mixed measurements from phasor measurement units (PMUs) and remote terminal units (RTUs), a delayed measurement model is constructed. A modified state estimator based on the Kalman filter (KF) is designed, which can obtain the optimal estimated states under measurement delays. Moreover, the measurement data transmitted from the sensor to the estimator are vulnerable to cyberattacks. Especially, false data-injection (FDI) attacks are frequently encountered in the power system state estimation (PSSE) process. In the case of measurement delays, an FDI attack strategy is designed to interfere with the state estimator and evade detection by the chi-square detector. By utilizing the attacked estimated information and the uncorrupted measurement information, two measurement residual vectors are designed. According to these two residual vectors, a chi-square-based attack detection method is proposed, which has the ability to detect the attack without being affected by the delayed measurements. The proposed KF algorithm and attack detection method are implemented on an IEEE 14-bus system and they are confirmed to be effective and feasible.

中文翻译：

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具有测量延迟的电力系统动态估计的安全性分析


本文主要针对具有测量延迟的电力系统动态状态估计的网络安全研究。依靠相量测量单元（PMU）和远程终端单元（RTU）的混合测量，构建延迟测量模型。设计了一种基于卡尔曼滤波器（KF）的修正状态估计器，能够在测量延迟的情况下获得最优的估计状态。此外，从传感器传输到估计器的测量数据容易受到网络攻击。特别是，在电力系统状态估计（PSSE）过程中经常遇到虚假数据注入（FDI）攻击。在测量延迟的情况下，FDI 攻击策略被设计为干扰状态估计器并逃避卡方检测器的检测。利用受攻击的估计信息和未损坏的测量信息，设计了两个测量残差向量。根据这两个残差向量，提出了一种基于卡方的攻击检测方法，该方法能够检测攻击而不受延迟测量的影响。所提出的KF算法和攻击检测方法在IEEE 14总线系统上实现，并被证明是有效和可行的。