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A discrete-event simulation approach to evaluate the effect of stochastic parameters on offshore wind farms assembly strategies
Muhabie, Y.T.; Rigo, P.; Cepeda, M.; D'Agosto, M.D.A.; Caprace, J.-D. (2018). A discrete-event simulation approach to evaluate the effect of stochastic parameters on offshore wind farms assembly strategies. Ocean Eng. 149: 279-290. https://hdl.handle.net/10.1016/j.oceaneng.2017.12.018
In: Ocean Engineering. Pergamon: Elmsford. ISSN 0029-8018; e-ISSN 1873-5258
Peer reviewed article  

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Trefwoord
    Marien
Author keywords
    Offshore; Logistics; Simulation; Stochastic processes; Decision supportsystems; Metocean

Auteurs  Top 
  • Muhabie, Y.T.
  • Rigo, P.
  • Cepeda, M.
  • D'Agosto, M.D.A.
  • Caprace, J.-D.

Abstract
    The 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.

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