Aiming at the problems of poor adaptability to complex terrain, low inspection efficiency and high energy consumption existing in the path planning of UAVs for transmission and distribution line inspection in plateau and mountainous substations, an autonomous flight path optimization strategy for UAVs based on DBO (dung beetle optimizer) was proposed to address these issues. The biological behavior of dung beetles rolling dung balls is simulated by the algorithm. A three-layer optimization model that integrates global search, local exploitation and obstacle avoidance was constructed. Meanwhile, a dynamic step size adjustment mechanism and an elite retention mechanism were introduced to improve the algorithm performance.Multi-constraint conditions for transmission and distribution line inspection, including endurance limits, terrain obstacles and signal coverage, were taken into account in this study. A multi-objective optimization function with the shortest path length and minimum energy consumption as objectives was established. Static and dynamic obstacles were introduced to achieve obstacle avoidance under various Scenarios. The pathfinding process was simplified to search for the optimal inspection path. Simulation experiments were conducted to verify the effectiveness of the proposed algorithm. Results show that the path optimization effect of this algorithm in complex terrain outperforms that of PSO (particle swarm optimization) and GA (genetic algorithm). It provides an efficient path planning scheme for intelligent inspection systems.