A bad data detection algorithm in power system state estimation

1978 ◽  
Vol 98 (5) ◽  
pp. 108-115
Author(s):  
Hiroshi Sasaki ◽  
Masao Nakashima ◽  
Yoshinao Tamaru
Keyword(s):  
Power System ◽  
State Estimation ◽  
Detection Algorithm ◽  
Data Detection ◽  
System State ◽  
Power System State Estimation ◽  
Bad Data Detection ◽  
Bad Data

Bad data detection in power system state estimation based on generalized likelihood ratio test

2016 ◽  
Vol 04 (04) ◽  
pp. 1650016 ◽  
Author(s):  
Zahid Khan ◽  
Radzuan B. Razali ◽  
Hanita Daud ◽  
Nursyarizal Mohd Nor ◽  
Mahmud Fotuhi-Firuzabad ◽  
...  
Keyword(s):  
Power System ◽  
State Estimation ◽  
Likelihood Ratio Test ◽  
Generalized Likelihood Ratio Test ◽  
Data Detection ◽  
Ratio Test ◽  
System State ◽  
Power System State Estimation ◽  
Bad Data Detection ◽  
Bad Data

scholarly journals A Novel Detection Algorithm to Identify False Data Injection Attacks on Power System State Estimation

Energies ◽  
2019 ◽  
Vol 12 (11) ◽  
pp. 2209 ◽  
Author(s):  
Mehdi Ganjkhani ◽  
Seyedeh Narjes Fallah ◽  
Sobhan Badakhshan ◽  
Shahaboddin Shamshirband ◽  
Kwok-wing Chau
Keyword(s):  
Neural Network ◽  
Power System ◽  
State Estimation ◽  
Data Detection ◽  
System State ◽  
Power System State Estimation ◽  
Bad Data Detection ◽  
False Data Injection ◽  
Injection Attacks ◽  
Bad Data

This paper provides a novel bad data detection processor to identify false data injection attacks (FDIAs) on the power system state estimation. The attackers are able to alter the result of the state estimation virtually intending to change the result of the state estimation without being detected by the bad data processors. However, using a specific configuration of an artificial neural network (ANN), named nonlinear autoregressive exogenous (NARX), can help to identify the injected bad data in state estimation. Considering the high correlation between power system measurements as well as state variables, the proposed neural network-based approach is feasible to detect any potential FDIAs. Two different strategies of FDIAs have been simulated in power system state estimation using IEEE standard 14-bus test system for evaluating the performance of the proposed method. The results indicate that the proposed bad data detection processor is able to detect the false injected data launched into the system accurately.

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