A novel task allocation and path planning algorithm with maximum endurance constraints is proposed for the problem of multi-UAV task allocation and path planning in electric power inspection. Firstly, the jump point search （JPS) algorithm is introduced based on the auction mechanism to estimate the shortest obstacle avoidance path lengths between UAVs and tasks and between tasks and tasks, effectively addressing the coupling problem of task allocation and path planning. Secondly, the maximum endurance constraint of UAVs is integrated into the optimization objective function to ensure that UAVs can complete the assigned inspection tasks within their maximum endurance capacities. Finally, a lazy auction strategy is proposed to speed up the algorithm's convergence without compromising the solution quality of task allocation. The simulations show that the proposed method is more suitable for the operational requirements of multirotor UAVs with limited endurance than existing methods. Moreover, the time needed to solve the task allocation is reduced by nearly 40%. The experiments demonstrate the practicality and effectiveness of the proposed method.