Cost-effectivity of logistical strategies for the installation of offshore wind turbine substructures

Abstract

The ever-increasing size of offshore wind turbine substructures and the development of wind farms at sites further offshore, with greater water depths and with extremer weather conditions, raise logistical challenges that have never been faced before. Additionally, the offshore wind industry has to deal with governments cutting subsidies, small profit margins and limited practice guidelines, while it is expected to lower the associated levelised cost of energy to a competitive level in the market. Scientific studies have identified room for optimisation in the substructure (the focus is laid on Monopiles (MPs) with Transition Pieces (TPs) and pre-piled jackets) transportation and installation phases. However, no studies that evaluate the performance of strategies for these phases are identified. Hence, the objective of this study is to “generate insights into the complex system of interdependent strategies for the installation of offshore wind turbine substructures, and to identify and quantify cost-reduction opportunities.” The considered strategies are formed by combinations of transportation and installation strategies, which differentiate based on the number and type of the deployed vessels and the sequence in which the operations are performed.

To quantitatively compare the strategies, and to consider stochastic processes (e.g., weather conditions), a discrete-event simulation modelling approach is adopted. To arrive at substantiated conclusions, a framework is followed, which provides a roadmap and rigour criteria for the design, implementation and evaluation phases. First, a conceptual model is developed and face validated. Next, a numerical “base model” is constructed, which describes the most basic strategy. This model is face validated by industry experts and evaluated by parameter variability, convergence and historical data validation tests. It is concluded that the base model is structured according to shared practical experiences, responds satisfactory to parameter changes, requires 35 simulation runs to converge, and has good predictive capabilities. Hence, it is deemed suitable to function as a “template” for the modelling of the other strategies.

The simulation results are evaluated for each of the considered substructures separately. (i) MP – TP installation. In general, assembly-line installation strategies, in which two Heavy Lift Vessels (HLVs) are deployed, are associated with the shortest installation time. The shuttling – assembly-line and the shuttling–alternating (in which MPs and TPs are installed alternatingly) strategies are associated with the lowest costs. Both involve a shuttling transportation strategy, in which the HLV(s) ensure(s) both the transportation and installation of the components. The mooring of barges alongside an HLV in feeder strategies (feeder vessels supply components to an HLV, which stays at the wind farm under development) and the installation of TPs by a relatively small HLV in assembly-line strategies are identified as the main bottlenecks. Reducing these by relatively simple solutions can result in significant performance increases. Lastly, the project start date is found to be a strong determinant of strategy performance. (ii) Jacket – foundation pile installation. The assembly-line strategies are found to result in the shortest jacket installation times as well. However, only the shuttling – assembly-line strategy is additionally associated with the lowest costs. Furthermore, it is found that a separate pile-dredging vessel can help to reduce the time and costs associated with separate phases installation strategies, in which jackets and their foundation piles are installed in different phases. Also for jackets, the barge mooring alongside the HLV is identified to be the largest bottleneck. Reducing this bottleneck can result in significant performance benefits. Lastly, a relationship is found between the performance of jacket installation strategies and the project start date, although weaker than for MP installation.

The developed decision support tool can provide a platform for further research into the logistics of offshore wind and other industries, whereas the obtained results are only valid within the set boundaries. To widen the applicability, it is recommended to perform follow-up studies in which a stochastic mechanical failure component is included, and the sensitivity to the wind farm size and port-to-farm distance is tested. Furthermore, it is advised to extend this study to investigate the potential of the industry adopting a more holistic process or market point of view.