Abstract: The resilience assessment of power systems can reflect their ability to resist and recover from extreme events. To improve the resilience assessment method for power systems under snow and ice disaster weather, proposes a framework for resilience assessment of power systems under extreme snow and ice disaster weather. Firstly, the resilience curve is analyzed to construct resilience assessment indicators for the entire stage of disaster, emergency repair, and recovery of the power system in the face of disasters. Secondly, based on the characteristics of snow and ice weather, the ice thickness on the conductors that changes over time is predicted, and the conductor stress is assessed based on the predicted ice thickness. Subsequently, a transmission line fault model is constructed, and a fault set is generated based on this fault model. Finally, considering factors such as the location of faulty components, maintenance teams, and load importance, a load recovery model with the fastest recovery speed for the power system is constructed. The simulated annealing optimization algorithm is used to solve the problem, and the optimal emergency repair strategy is obtained. Taking the IEEE 15-bus system as an example, the feasibility of the proposed assessment method is verified. This resilience assessment method can accurately and comprehensively consider the impact of various factors on the resilience of the power grid. The simulation results show that the use of this algorithm for emergency repair strategy allocation improves by 2.88% compared to traditional emergency repair strategies, providing a reference for the quantification and resilience improvement of the power sector in the future.