In this paper, a method for stochastic analysis of an offshore wind farm using computational fluid dynamics (CFD) is proposed. An existing offshore wind farm is modelled using a steady-state CFD solver at several deterministic input ranges and an approximation model is trained on the CFD results. The approximation model is then used in a Monte-Carlo analysis to build joint probability distributions for values of interest within the wind farm. The results are compared with real measurements obtained from the existing wind farm to quantify the accuracy of the predictions. It is shown that this method works well for the relatively simple problem considered in this study and has potential to be used in more complex situations where an existing analytical method is either insufficient or unable to make a good prediction.
|Number of pages||10|
|Journal||Journal of Physics: Conference Series|
|Publication status||Published - 19 Jun 2018|
|Event||7th Science of Making Torque from Wind, TORQUE 2018 - Milan, Italy|
Duration: 20 Jun 2018 → 22 Jun 2018
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ASJC Scopus subject areas
- Physics and Astronomy(all)