Spectral analysis based robust multi-level intrusion detection in wide area frequency control

Frequency control is one of the critical systems responsible for maintaining grid stability, making it an attractive choice for cyber-attacks. The paper presents a singular spectrum analysis for extracting the system's dynamics under regular operation and proposes a projection-based distance tracking method to detect Multi-area Load Frequency Control (MA-LFC) attacks. Two variations of the algorithm, namely single-variate and multi-variate algorithms, are proposed for detection at different levels of the power system. The proposed methodology is robust, adaptive, and computationally efficient, especially when system and measurement noises are considered. The method's main advantage is that it does not require attack data and can be integrated with the existing grid control system. The algorithm can be implemented within the RTUs/IEDs without the need for additional processors. The detection algorithm successfully detects different types of attacks, including stealth attacks on multiple sensors. By selecting proper set of signals, it is possible to obtain 99.85% accuracy and 2 cycles deduction speed. The algorithm is tested on an IEEE 39-bus New England test system in the MATLAB environment, and its performance under noisy measurements is better than existing methods.