DocumentCode
2069120
Title
On the nonlinearity effects on malicious data attack on power system
Author
Liyan Jia ; Thomas, R.J. ; Lang Tong
Author_Institution
Sch. of Electr. & Comput. Eng., Cornell Univ., Ithaca, NY, USA
fYear
2012
fDate
22-26 July 2012
Firstpage
1
Lastpage
8
Abstract
There has been a growing literature on the malicious data attack (or data injection attack) on power systems. Most existing work focuses on the DC (linear) model with linear state estimators. This paper examines the effects of nonlinearity in the power systems on the effectiveness of malicious data attack on state estimation and real-time market. It is demonstrated that attack algorithms designed for the DC model may not be effective when they are applied to nonlinear system with nonlinear state estimators. Discussion and experiments results about nonlinearity are provided.
Keywords
power markets; power system security; power system simulation; DC model; data injection attack; linear model; malicious data attack; nonlinear state estimators; nonlinear system; nonlinearity effects; power systems nonlinearity; real-time market; state estimation; Detectors; Electricity supply industry; Nonlinear systems; Power systems; Real-time systems; State estimation; Vectors; Bad Data Detection; Electricity Market; Malicious Data Attack; Nonlinear System; State Estimation;
fLanguage
English
Publisher
ieee
Conference_Titel
Power and Energy Society General Meeting, 2012 IEEE
Conference_Location
San Diego, CA
ISSN
1944-9925
Print_ISBN
978-1-4673-2727-5
Electronic_ISBN
1944-9925
Type
conf
DOI
10.1109/PESGM.2012.6345685
Filename
6345685
Link To Document