Impact analysis of false data injection attacks on power system static security assessment

Static security assessment(SSA) is an important procedure to ensure the static security of the power system.Researches recently show that cyber-attacks might be a critical hazard to the secure and economic operations of the power system. In this paper, the influences of false data injection attack(FDIA) on the power system SSA are studied. FDIA is a major kind of cyber-attacks that can inject malicious data into meters, cause false state estimation results, and evade being detected by bad data detection. It is firstly shown that the SSA results could be manipulated by launching a successful FDIA, which can lead to incorrect or unnecessary corrective actions. Then,two kinds of targeted scenarios are proposed, i.e., fake secure signal attack and fake insecure signal attack. The former attack will deceive the system operator to believe that the system operates in a secure condition when it is actually not. The latter attack will deceive the system operator to make corrective actions, such as generator rescheduling, load shedding, etc. when it is unnecessary and costly. The implementation of the proposed analysis is validated with the IEEE-39 benchmark system.

Data-driven Probabilistic Static Security Assessment for Power System Operation Using High-order Moments

In this letter,a new formulation of Lebesgue integration is used to evaluate the probabilistic static security of power system operation with uncertain renewable energy generation.The risk of power flow solutions violating any pre-defined operation security limits is obtained by integrating a semialgebraic set composed of polynomials.With the high-order moments of historical data of renewable energy generation,the integration is reformulated as a generalized moment problem which is then relaxed to a semi-definite program(SDP).Finally,the effectiveness of the proposed method is verified by numerical examples.