Predicting the benefit of wake steering on the annual energy production of a wind farm using large eddy simulations and Gaussian process regression

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Abstract

In recent years, wake steering has been established as a promising method to increase the energy yield of a wind farm. Current practice in estimating the benefit of wake steering on the annual energy production (AEP) consists of evaluating the wind farm with simplified surrogate models, casting a large uncertainty on the estimated benefit. This paper presents a framework for determining the benefit of wake steering on the AEP, incorporating simulation results from a surrogate model and large eddy simulations in order to reduce the uncertainty. Furthermore, a time-varying wind direction is considered for a better representation of the ambient conditions at the real wind farm site. Gaussian process regression is used to combine the two data sets into a single improved model of the energy gain. This model estimates a 0.60% gain in AEP for the considered wind farm, which is a 76% increase compared to the estimate of the surrogate model.

Original languageEnglish
Article number022024
Number of pages10
JournalJournal of Physics: Conference Series
Volume1618
Issue number2
DOIs
Publication statusPublished - 2020
EventScience of Making Torque from Wind 2020, TORQUE 2020 - Online, Virtual, Online, Netherlands
Duration: 28 Sep 20202 Oct 2020

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