Risk Assessment of Malicious Attacks on a Power System with High Penetration of Renewables

Power system risk in case of undesired events is impacted by uncertain renewable generations. In this paper, the risk different types of malicious attacks carry on power systems is investigated for a system with a high penetration of renewable generations. A linear model is presented and incorporated in a stochastic programming to reduce the risk against non-intelligent attacks. Another linear model is also presented and included in a robust optimization to minimize the risk against intelligent malicious attacks. The energy and reserve powers of generation units are simultaneously scheduled in the proposed models. The methods are applied on test systems, and the results are discussed.