Abstract: As the importance of power networks increases in the aftermath of catastrophic events,rapid and accurate assessment of network damage has become critical.Unmanned aerial vehicles (UAVs),owing to their aerial flexibility and autonomy,have emerged as effective tools for power network inspection.This study proposes a UAV-based evaluation method for distribution networks that integrates wireless charging and dynamic route optimization to improve assessment efficiency and ensure continuous UAV operation.An optimization model is developed based on multi-objective mixed-integer linear programming (MILP)to dynamically determine the UAVs'optimal flight paths and speeds,thereby maximizing data collection efficiency while minimizing the time required for inspection.In addition,the model incorporates wireless energy replenishment during flight to ensure UAVs can complete the entire network evaluation.Simulation experiments conducted on a distribution network with 77nodes and 73lines validate the effectiveness of the proposed approach.The results demonstrate that the method significantly improves the efficiency and accuracy of power network damage assessment.