With the rapid development of unmanned aerial vehicle (UAV) technology, UAVs are widely used in inspection tasks of various fields. In recent years, the scale and length of power networks have been growing rapidly, and UAVs have become the first choice for power inspection due to their unique performance and advantages. They can not only ensure safety, but also effectively improve inspection efficiency. Regarding inspection tasks, the path planning of UAVs is crucial in practical application. In this paper, a new hybrid meta-heuristic algorithm is proposed to solve the UAVs routing planning problem with multiple depots in power inspection. In the framework of adaptive large neighborhood search, the variable neighborhood descent strategy is added to enhance the neighborhood search ability and increase the possibility of finding a better solution. Experimental results show that the proposed algorithm can effectively solve the problem and has good stability and robustness. In addition, the proposed algorithm is compared with other meta-heuristic algorithms experimentally, and the comparison results verify that this algorithm can effectively reduce the number and time cost of UAVs used in inspection.