Optimization Method for Remote Inspection Path Planning of Secondary Equipment Based on Chaotic Genetic Algorithm

Remote inspection of secondary equipment is an important task in the operation and maintenance of power systems. Reasonable planning of inspection paths can improve efficiency and safety. This article proposes an optimization method for remote inspection path planning of secondary equipment based on chaotic genetic algorithm. Firstly, construct a substation grid model to describe whether there are obstacles in the remote inspection workspace of secondary equipment in the substation. On this basis, using chaotic genetic algorithm, the application process in path planning includes individual encoding, population initialization, selection operation, crossover and mutation operation, as well as chaotic search process, to achieve optimization of remote inspection path planning for secondary equipment in substations. The experimental results show that this method has made significant improvements in improving the efficiency of remote inspection of secondary devices and path quality, and has better performance compared to traditional methods.