A Two-stage Kalman Filter for Cyber-attackDetection in Automatic Generation Control System

 Name of the Journal: JOURNAL OF MODERN POWER SYSTEMS AND CLEAN ENERGY

Title of the article:  A Two-stage Kalman Filter for Cyber-attack Detection in Automatic Generation Control System

Abstract:

Communication plays a vital role in incorporating smartness into the interconnected power system network. How‐ever, historical records prove that the data transfer has always been vulnerable to cyber-attacks. Unless these attacks are identified and cordoned off, it may lead to black-out resulting in national security issues. This paper proposes an optimal two-stage Kalman filter (OTS-KF) for simultaneous state and attack estimation in Automatic generation control (AGC) system. Bias/at‐tacks  are  modeled  as  unknown  inputs  in  the AGC  dynamics.Five types of attacks namely False Data Injection (FDI), Data Replay Attack, Denial of Service (DoS), scaling, and ramp at‐tacks are injected in the measurements and are estimated using OTS-KF. As the load variations of each area are seldom avail‐able, OTS-KF is reformulated to estimate the states and outliers along with the load variations on the system. The proposed idea is validated on a benchmark two-area, three-area, and five-area  power system  models. The  simulation  results  under various test conditions show the efficacy of the proposed filter.

Link: Full Paper

Ayyarao, Tummala SLV, and I. Ravi Kiran. "A Two-Stage Kalman Filter for Cyber-Attack Detection in Automatic Generation Control System." Journal of Modern Power Systems and Clean Energy (2021).