The first large offshore wind farms installed in the North Sea Region (NSR) soon reach their technical end of lifetime. The wind turbines in these farms will have to be decommissioned after power production has stopped. Currently offshore wind turbines are decommissioned based on a method called reversed installation, a time consuming and therefore costly operation. This report focuses on the situation regarding decommissioning of offshore wind turbines (excluding foundations), and unveils the possibilities of potential decommissioning methods, using a jack-up, in an effort of to obtain a more cost-effective and environmentally friendly method than the currently used reversed installation. The act of decommissioning is explained, together with the expected market of decommissioning in the North Sea Region. Legislation concerning decommissioning of the five largest offshore wind producing countries in Europe are discussed. Using a multi criteria analysis on demolition methods, floating alternatives, and a model (determining the transport configuration), the most economical and least energy consuming combination is chosen. This model shows an economization of up to 66% and cutting the energy consumption by a third. Lastly, these outcomes are applied to three separate business cases including a sensitivity analysis to show the effect that variations in input values have on the results.

During the lifetime of an offshore wind farm, the operation and maintenance (O&M) costs account for a large portion of the total expenses. This is mainly caused by the high cost of vessels. In order to increase the competitiveness of offshore wind compared to onshore wind and other renewable energy sources, it is essential to decrease the cost of power generation of offshore wind. In this context, the scope of this research is the optimization of fleet management decisions, often referred to as the fleet size and mix problem, for the maintenance of offshore wind farms. Therefore, the literature on available solution methods and existing models have been reviewed first. Based on a comparison of the existing models, a simulation model is developed and presented in this report. The developed methodology is illustrated with a case study example. The model is verified by comparing the expected and actual results of various verification experiments. Moreover, several sensitivity analyses are performed. In the last section of this report, recommendations for features that can be added to the model are given. The developed methodology can be used to optimize fleet management decisions for a given maintenance strategy and, in addition, the consequences of various decisions can be evaluated since the model predicts the O&M costs and wind farm power production.