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

作　　者：Ayyarao S.L.V.Tummala Ravi Kiran Inapakurthi 

机构地区：[1]GMR Institute of Technology,Rajam,Srikakulam,Andhra Pradesh,India [2]Raghu Engineering College,Dakamarri,Visakhapatnam,Andhra Pradesh,India

出　　处：《Journal of Modern Power Systems and Clean Energy》2022年第1期50-59,共10页现代电力系统与清洁能源学报（英文）

摘　　要：Communication plays a vital role in incorporating smartness into the interconnected power system.However,historical records prove that the data transfer has always been vulnerable to cyber-attacks.Unless these cyber-attacks are identified and cordoned off,they may lead to black-out and result in national security issues.This paper proposes an optimal two-stage Kalman filter(OTS-KF)for simultaneous state and cyber-attack estimation in automatic generation control(AGC)system.Biases/cyber-attacks are modeled as unknown inputs in the AGC dynamics.Five types of cyber-attacks,i.e.,false data injection(FDI),data replay attack,denial of service(DoS),scaling,and ramp attacks,are injected into the measurements and estimated using OTS-KF.As the load variations of each area are seldom available,OTS-KF is reformulated to estimate the states and outliers along with the load variations of the system.The proposed technique is validated on the benchmark two-area,three-area,and five-area power system models.The simulation results under various test conditions demonstrate the efficacy of the proposed filter.

关 键 词：Cyber-security automatic generation control(AGC) load frequency control false data injection cyber-attack detection 

分 类 号：TM73[电气工程—电力系统及自动化] TP393.08[自动化与计算机技术—计算机应用技术]