Spoofing Attack Detection for Radar Network System State Estimation

2019 ◽  
pp. 21-33
Author(s):  
Tianqi Huang ◽  
Buhong Wang ◽  
Dong Lin
Keyword(s):  
State Estimation ◽  
Attack Detection ◽  
Network System ◽  
System State ◽  
Radar Network

scholarly journals Cyber-attack Detection Strategy Based on Distribution System State Estimation

2020 ◽  
Vol 8 (4) ◽  
pp. 669-678
Author(s):  
Huan Long ◽  
Zhi Wu ◽  
Chen Fang ◽  
Wei Gu ◽  
Xinchi Wei ◽  
...  
Keyword(s):  
State Estimation ◽  
Distribution System ◽  
Attack Detection ◽  
Cyber Attack ◽  
System State ◽  
Detection Strategy

POWER SYSTEM STATE ESTIMATION USING A ROBUST ESTIMATOR

2019 ◽  
Vol XVI (4) ◽  
pp. 53-65
Author(s):  
Zahid Khan ◽  
Katrina Lane Krebs ◽  
Sarfaraz Ahmad ◽  
Misbah Munawar
Keyword(s):  
Power Systems ◽  
State Estimation ◽  
Loss Function ◽  
Weighted Least Squares ◽  
Primary Data ◽  
Robust Estimator ◽  
System State ◽  
State Estimator ◽  
Suggested Approach ◽  
Power System State Estimation

State estimation (SE) is a primary data processing algorithm which is utilised by the control centres of advanced power systems. The most generally utilised state estimator is based on the weighted least squares (WLS) approach which is ineffective in addressing gross errors of input data of state estimator. This paper presents an innovative robust estimator for SE environments to overcome the non-robustness of the WLS estimator. The suggested approach not only includes the similar functioning of the customary loss function of WLS but also reflects loss function built on the modified WLS (MWLS) estimator. The performance of the proposed estimator was assessed based on its ability to decrease the impacts of gross errors on the estimation results. The properties of the suggested state estimator were investigated and robustness of the estimator was studied considering the influence function. The effectiveness of the proposed estimator was demonstrated with the help of examples which also indicated non-robustness of MWLS estimator in SE algorithm.

Conditionally minimax algorithm for nonlinear system state estimation

1994 ◽  
Vol 39 (8) ◽  
pp. 1617-1620 ◽  
Author(s):  
A.R. Pankov ◽  
A.V. Bosov
Keyword(s):  
Nonlinear System ◽  
State Estimation ◽  
System State

MODEL‐BASED ANOMALY DETECTION FOR POWER SYSTEM STATE ESTIMATION

2020 ◽  
pp. 99-121
Author(s):  
Aditya Ashok ◽  
Manimaran Govindarasu ◽  
Venkataramana Ajjarapu
Keyword(s):  
Anomaly Detection ◽  
Power System ◽  
State Estimation ◽  
System State ◽  
Power System State Estimation ◽  
Model Based

Power System State Estimation: Detection of Topological Errors

1981 ◽  
Vol PER-1 (1) ◽  
pp. 19-19
Author(s):  
R. L. Lugtu ◽  
D. F. Hackett ◽  
K. C. Liu ◽  
D. D. Might
Keyword(s):  
Power System ◽  
State Estimation ◽  
System State ◽  
Power System State Estimation ◽  
Topological Errors
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