A B S T R A C TThe wind industry is facing new challenges due to the planned construction of thousands of offshore wind turbines all around the world. However, with their increasing distance from the shore, greater water depths, and increasing sizes of the plants, the industry has to face the challenge to develop sustainable installation procedures. Important limiting factors for offshore wind farm installation are the weather conditions and installation strategies. In this context, the focus of this research is the investigation of the most effective approach to installing offshore wind farms at sea, including the effects of weather conditions. This target is achieved through the implementation of a discrete-event simulation approach which includes the analysis of the environmental conditions, distance matrix, vessel characteristics, and assembly scenarios. The model maps the logistics chain in the offshore wind industry. A deterministic and a probabilistic metocean data method have been compared and cross validated. The results point to a good agreement between the two considered models, while highlighting the huge risks to the time and cost of the installation due to the stochastic nature of the weather. We suggest that simulations may improve and reduce these risks in the planning process of offshore wind farms.

The offshore wind energy development is highly affected by the condition of the weather at sea. Hence, it demands a well-organized planning of the overall process starting from the producers’ sites until the offshore site where the turbines will finally be installed. The planning phase can be supported with the help of Discrete Event Simulation (DES) where weather restrictions, distance matrix, vessel characteristics and assembly scenarios are taken into account. The purpose of this paper is to simulate the overall transport, assembly and installation of the wind turbine components at sea. The analysis is carried out through DES considering both the real historical weather data (wind speed and wave height) and probabilistic approach. Results of the study, applied to the real Offshore Wind Farm (OWF) configuration, are showing a good agreement between the two proposed models. The results point out that the probabilistic\ approach is highly affected by the semi-random numbers used to model the stochastic behavior of the input variable so that several iterations (200 to 400) are required to reach the convergence of the simulation outputs. We suggest that seasonality of the outputs of both models are preserved, i.e. the variation of the results depending on the variation of the weather along the year. These findings provide a new framework to address risks and uncertainties in OWF installations.