With the development of society and the requirements for clean energy, offshore wind farms (OWFs) that can generate steady and continuous electricity have been built. With harsher weather conditions and more powerful wind resources, the wind turbines at offshore wind farms are significantly larger than those at onshore wind farms. The complex weather conditions and mechanical structure of wind turbines pose problems for their operation and maintenance (O&M).
The cost of vessel chartering significantly contributes to the overall cost of operating and maintaining an offshore wind farm. By selecting the optimal fleet mix for executing the maintenance, the vessel chartering cost can be reduced, reducing the operation and maintenance costs of the offshore wind farm. This reduces the levelized cost of energy from the offshore wind farm. This report developed a simulation and optimization model based on mixed integer linear programming to determine the opti-mal fleet mix for executing the maintenance tasks by minimizing the vessel acquisition cost. The Monte Carlo simulation is implemented to statistic an optimal strategy for chartering the vessels.
Chapter 1 introduces the offshore wind farm (OWF) and its operation and maintenance (O&M) activi-ties. Chapter 2 provided a literature review on the latest progress of the offshore wind farm’s operation and maintenance. Chapter 3 provides a simulation model for component wear, maintenance require-ment generation, and maintenance task execution. The process of optimization is explained in detail. Chapter 4 presents the mathematical model of the optimizer, which arranges the vessels and executes maintenance tasks. Chapter 5 presents a case study based on the latest progress data. The Monte Carlo simulation yields the optimal initial purchased fleet mix derived based on the Monte Carlo simu-lation. Finally, Chapter 6 gives the conclusion and recommendations for future studies.