A Bilevel Optimization Model for Risk Assessment and Contingency Ranking in Transmission System Reliability Evaluation

This paper presents a bilevel optimization model for the risk assessment of transmission systems. Specifically, the lower level model is expected to provide a generation redispatch by minimizing the total load shedding, and the upper-level model is to maximize the severity risk by constructing a binary optimization model to identify the worst N-k contingency. To further reduce the complexity of the proposed model, the logarithmic transformation and linearization techniques are utilized, leading to a general mixed integer linear programming. In addition, a recursive method is proposed for contingency ranking based on the bilevel optimization model. Compared with the benchmark analytic method, the proposed method does not need to enumerate every contingency, reducing the computational burden. In contrast to the traditional Monte Carlo Simulation method, the proposed method can give as precise a risk assessment result as the analytic method and has higher evaluation efficiency. Numerical results on three test systems verify the effectiveness of the proposed method.