Multi UAV Inspection Optimization for Offshore Wind Farms Considering Battery Exchange Process

Unmanned Aerial Vehicles (UAVs) have become a highly effective tool for inspecting Offshore Wind Farms (OWFs) due to their controllability, speed, and safety. A practical route planning program ensures timeliness of UAV OWFs inspection. The previous studies' models do not reflect real-world constraints of battery exchange operation-based UAV multistrip flights within UAV range and airport deployments. In this paper, an OWF inspection tasks allocation problem of UAVs (OWFI-TAP-of UAVs) is analyzed, which considers the UAV battery exchange process. Firstly, the UAV model to calculate the inspection time consumption is established, which considers the relation between UAV velocity and energy and the battery exchange process; then, a multi-UAV inspection task allocation model for minimizing the UAV inspection time by combining the Multiple Traveling Salesman Problem (MTSP) mathematical expressions and the battery exchange specificities is proposed. Secondly, an improved genetic algorithm (IGA) is proposed that includes a clustering initialization strategy and a task balance strategy to optimize the OWFI-TAP-of UAVs globally. Finally, taking Jiaxing OWF as the simulation case through numerical experiments validates the effectiveness of the proposed approach.