INVESTIGATION OF FALSE DATA INJECTION IN SMART GRID TO MINIMIZE THE SECURITY RISKS IN AGC release_w2gixkclvzawlfvldxstdcgpre

Abstract

In smart grid, when the false data is injected to electronic monitoring system, the AGC will directly affects and potentially leads to blackouts. The main objective of this paper is to examine the attacks due to injection of false data in smart grid for the purpose of minimizing the risks in AGC. In the previous research, the Intrusion Detection System was used, in which they implemented Intrusion Detection Algorithm for the grid security system. But this method can't be employed often due to mathematical complexity and difficulty in practical implementation. This paper presents a Game-Theory based method for the security of smart grid by relating the quantifiable risk managing techniques with decision making for protective measures. The significances of the injected data attacks are computed using risk assessment process. The calculated risks are then unified into the stochastic (Markov) security game classic as input parameters. The decisions of protective measures are attained by resolving the game using dynamic programming approach which considers the resource constraints. The Nash equilibrium results are used to acquire the Game Matrix. The simulation result indicates that the different risk events will leads to different security approaches. The attacker-defender interaction and the AGC risk minimization are validated through extensive simulation results using MATLAB/SIMULINK.
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