Abstract: To enhance the efficiency and reliability of UAV-based ultraviolet (UV) inspection in smart grids and address the shortcomings of traditional path planning methods in complex terrains and discharge source regions,this paper proposes a path optimization strategy combining an improved A^* algorithm with a genetic algorithm.A 3D multi-objective path planning model is established based on UV discharge characteristics,incorporating a composite cost function that accounts for flight distance,altitude variation,path smoothness,obstacle avoidance,and discharge source evasion.An improved A^* algorithm is designed by introducing penalty terms for terrain elevation and discharge source distribution into the heuristic function to guide the generation of an initial path suitable for power grid scenarios.This path is then used as a heuristic individual in a genetic algorithm for global optimization,improving both search efficiency and path quality.Simulation experiments in typical mountainous transmission scenarios demonstrate that the algorithm outperforms traditional methods in terms of path length,obstacle avoidance,and discharge source coverage.The proposed approach significantly improves the rationality and completeness of UAV inspection paths and provides effective technical support for UV-based intelligent inspection in smart grids.

Key words: UAV inspection, path optimization, smart grid, dynamic adjustment strategy