Cascading fault path prediction of large-scale wind power grid-connected system based on bi-level multi-objective decision

The uncertainty of wind power output increases the difficulty of cascading fault path prediction. Therefore, this paper proposes a cascading fault path prediction method for large-scale wind power grid-connected system based on bi-level multi-objective decision. The probabilistic power flow model is used to describe the uncertain factors such as wind power output fluctuation and load fluctuation, and it is used as the calculation basis of cascading fault path prediction. A bi-level multi-objective decision-making model is proposed to determine the subsequent fault. The model takes the fault probability and fault consequence as the upper and lower decision-making objectives respectively, and determines the qualified cascading fault path set according to the Pareto optimal solution of the subsequent fault. The IEEE 39-bus system is taken as an example to verify the proposed method. The results show that the prediction method based on bi-level multi-objective decision can predict two types of cascading fault paths with high probability of occurrence and serious fault consequences at the same time, which is helpful to guide the prevention and control of cascading faults in large-scale wind power grid-connected systems.