Abstract
The safe operation of smart distribution network is highly dependent on the powerful technical guarantee provided by the function of information link, which makes the network vulnerable to the threat of malicious data injection and other network attacks during the operation. In order to ensure that this kind of malicious data injection attack can be detected sensitively in the operation of power grid, this paper proposes a kind of power system state estimation malicious data attack defense model based on historical data. Firstly, the Long Short-Term Memory(LSTM) network is trained with the historical state quantity to realize the state prediction model. The prediction results are used as a reference, and the deviation between the prediction and the real-time estimate is calculated to break the concealment of malicious data. Simulation results of IEEE33-bus power system verify the accuracy of prediction and the effectiveness of the proposed method for online detection of hidden malicious data.
Highlights
With the construction of power grid automation system, reliable sensor network and its deep integration with ubiquitous information network and energy network, the traditional power grid is gradually transformed into a smart grid with wide cooperation between information system and physical system and autonomous behavior ability
The research of smart grid attack detection is of great significance
Liu Y. et al proposed the malicious data attack [1] for the first time in 2009, which made use of the loophole in the traditional bad data detection mechanism of the control center to induce the state estimation of the control center to produce a wrong estimation of the system state, causing the control center to give wrong instructions and affecting the operation of the power grid
Summary
With the construction of power grid automation system, reliable sensor network and its deep integration with ubiquitous information network and energy network, the traditional power grid is gradually transformed into a smart grid with wide cooperation between information system and physical system and autonomous behavior ability. The research of smart grid attack detection is of great significance. Liu Y. et al proposed the malicious data attack [1] for the first time in 2009, which made use of the loophole in the traditional bad data detection mechanism of the control center to induce the state estimation of the control center to produce a wrong estimation of the system state, causing the control center to give wrong instructions and affecting the operation of the power grid. The introduction of artificial intelligence technology provides a new idea for the study of malicious data injection attack detection. The deviation data between the Euclidean distance prediction information and the real-time estimation state change is described to detect malicious attacks
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
