|dc.description.abstract||Wind energy is among the fastest growing electricity generation systems in the world. However, the offshore wind industry is challenged with still being far more costly than conventional energy sources. Operation and maintenance (O\&M) can account for up to a third of the overall lifetime costs for an offshore wind farm. A reduction of these costs is therefore crucial in order for electricity production from offshore wind to be competitive in the market. This creates a demand for effective scheduling of the maintenance activities.
This thesis presents a static, deterministic model that utilizes weather forecasts to create schedules for multiple wind farms with a joint vessel fleet in order to minimize O\&M costs. These schedules contain information on which vessel that should visit which wind farm and which tasks the vessels should perform and at what time.
Due to the complexity of the problem, exact methods struggles to solve larger problems with a planning period of more than one shift within a reasonable time. Two different rolling horizon heuristics are therefore proposed. The heuristics solve the problem by iteratively LP-relaxing some parts of the planning period of the problem, and fixing the solutions for some of the variables that are not LP-relaxed. The performance of the two heuristics were evaluated by comparing solution time and solution quality with the solutions obtained from an exact model.
The exact model and the best performing heuristic were further tested in a dynamic setting by simulating the problem over a longer time horizon. The results showed that the exact model solved for a planning period of one shift performed better, both in terms of solution time and solution quality, than the heuristic solved for a planning period of two and three shifts. Simulations of the problem can provide valuable information when making strategic decisions for offshore wind farms. This is illustrated for two different strategic issues; deciding a vessel fleet size and mix by comparing comparing different vessel fleets, and analyzing the synergy effects of a joint vessel fleet for two wind farms compared to two separate vessel fleets.||