At the EERA DeepWind’18 conference in Trondheim, Norway, two contributions by AWESOME researchers received the ‘Best Poster Award’. The awards are an excellent acknowledgement of the high-quality research that is performed in the AWESOME project.
The award for ‘Best Communication’ went to Elena Gonzalez (CIRCE‑Universidad de Zaragoza), with her co‑authors Laura Valldecabres (ForWind‑University of Oldenburg), Helene Seyr (NTNU), Marcelo Martínez and Julio J. Melero (CIRCE‑Universidad de Zaragoza). Their work was entitled ‘On the effects of environmental conditions on wind turbine performance: an offshore case study’. The committee considered the relevance, originality, scientific content and presentation of the work. The authors studied the variability of wind turbine performance, through several SCADA operational parameters, during different environmental conditions, covering both wave and wind conditions. The results support the importance of using low data aggregation periods to understand the dynamics of wind turbine performance.
The award for ‘Best Content’ went to Lisa Ziegler (Ramboll, NTNU) with her co-authors Matthieu Rhomberg (Ramboll, NTNU, TU Delft) and Michael Muskulus (NTNU). Their paper was entitled ‘Design optimization with genetic algorithm: How does steel mass scale if offshore wind monopiles are designed for a longer service life?’. The award committee recognized the scientific originality of this work: The authors combined importance sampling with a genetic algorithm to reduce the number of load simulations during the optimization of a monopile. Results of a case study show that only 5% more steel mass are needed to rise the fatigue life of a monopile from 25 to 35 years. The publication is based on the work of Matthieu Rhomberg, who wrote his master thesis in collaboration with Ramboll, NTNU, and TU Delft.
In addition, Helene Seyr (NTNU) presented in the Operations & Maintenance Session the paper authored together with Michael Muskulus (NTNU) titled ‘Using a Langevin model for the simulation of environmental conditions in an offshore wind farm’. The authors investigated a novel approach to generating weather time series based on specific site conditions. They use a stochastic process, called the Langevin process. This new approach has fewer parameters than the existing ones and the properties of the weather are replicated reasonably well, most importantly the persistence of weather windows for maintenance.
EERA DeepWind’2018 is the 15th Deep Sea Offshore Wind R&D Conference. The event took place in Trondheim (Norway) between 17th and 19th of January 2018. The posters and presentation ae available from the conferences website: https://www.sintef.no/projectweb/eera-deepwind/2018-conference/
For further information, please contact the authors.
Lisa Ziegler: firstname.lastname@example.org
Elena Gonzalez: email@example.com
Helene Seyr: firstname.lastname@example.org