Development and Evaluation of Advanced Air Mobility Supported Logistics for Offshore Wind Energy with Agent-Based Simulation

Abstract

Offshore wind farm operations and maintenance rely on efficient logistics for personnel transfer and time-critical equipment delivery under environmental and operational constraints. The integration of uncrewed aerial vehicles (UAVs) introduces additional flexibility, but interactions between vehicles, dispatching, and mission timing are complex and difficult to assess analytically. This thesis develops an agent-based System-of-Systems simulation framework to evaluate offshore logistics concepts combining crew transfer vessels, helicopters, and VTOL-capable UAVs. A design of experiments is used to vary key parameters such as wind farm distance, fleet composition, maintenance durations, and stochastic material demands. Performance is assessed based on fleet energy consumption and enabled maintenance hours. Results indicate that UAV-supported strategies can reduce energy consumption and improve turbine availability. In particular, UAV-based spontaneous delivery of spare parts and tools shows strong potential as a near-term solution. Full UAV-based equipment transport can further increase maintenance activity but may lead to higher energy demand depending on UAV design and mission structure.