Optimization of ship-deployed AUVs synergisticscheduling for offshore wind turbines underwater foundations inspection

Abstract

Guided by the IMO’s GHG reduction strategy and the “dual-carbon” goal, offshore wind power has become vital in renewable energy, and more attention has been paid to the regular inspection of offshore wind turbines (OWTs). The Autonomous Underwater Vehicle (AUV) has significantly improved inspection, but the current technology limits it to independently perform long-distance and complex tasks. We propose a ship-deployed AUVs synergistic mode to cover larger area inspections in a shorter period. A mixed-integer programming model is developed to optimize the ships’ routes and schedule AUVs’ drop and pick-up time. An adaptive large neighborhood search heuristic based on constraint programming (ALNSCP) is developed for large-scale instances. The simulation instances-based computational experiments verify the superiority of the synergistic mode and solution method in improving inspection efficiency. Sensitivity analysis further reveals how AUV debugging time and allowed float time affect inspection efficiency and cost. The analysis of variants with limited deployable AUVs and soft time windows enhances the applicability of the proposed solution. This study can realize the efficiency of AUV utilization and provide decision support for OWTs underwater foundations inspection.