Articles | Volume 2, issue 2
https://doi.org/10.5194/wes-2-491-2017
https://doi.org/10.5194/wes-2-491-2017
Research article
 | 
26 Oct 2017
Research article |  | 26 Oct 2017

Development of a comprehensive database of scattering environmental conditions and simulation constraints for offshore wind turbines

Clemens Hübler, Cristian Guillermo Gebhardt, and Raimund Rolfes

Abstract. For the design and optimisation of offshore wind turbines, the knowledge of realistic environmental conditions and utilisation of well-founded simulation constraints is very important, as both influence the structural behaviour and power output in numerical simulations. However, real high-quality data, especially for research purposes, are scarcely available. This is why, in this work, a comprehensive database of 13 environmental conditions at wind turbine locations in the North and Baltic Sea is derived using data of the FINO research platforms. For simulation constraints, like the simulation length and the time of initial simulation transients, well-founded recommendations in the literature are also rare. Nevertheless, it is known that the choice of simulation lengths and times of initial transients fundamentally affects the quality and computing time of simulations. For this reason, studies of convergence for both parameters are conducted to determine adequate values depending on the type of substructure, the wind speed, and the considered loading (fatigue or ultimate). As the main purpose of both the database and the simulation constraints is to compromise realistic data for probabilistic design approaches and to serve as a guidance for further studies in order to enable more realistic and accurate simulations, all results are freely available and easy to apply.

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Short summary
For the design of offshore wind turbines, the knowledge of environmental conditions is important. However, real high-quality data are rare. This is why a comprehensive database of environmental conditions at wind turbine locations in the North and Baltic Sea is derived using real data. The main purpose of this work is to collect realistic data for probabilistic approaches. Hence, all results are freely available.
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