Accurate yield estimations are necessary to prove the financial viability of wind farms in early-phase design. Due to the long time period between sea bed lease auctions and the decommissioning of wind farms, uncertainties in wind farm properties and atmospheric conditions arise.
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Accurate yield estimations are necessary to prove the financial viability of wind farms in early-phase design. Due to the long time period between sea bed lease auctions and the decommissioning of wind farms, uncertainties in wind farm properties and atmospheric conditions arise. Wake steering is a wind farm flow control technology that was shown to have a substantial impact on annual energy production (AEP) in many field experiments; however, the accuracy of the AEP uplift estimated during the uncertain, early design phase is unknown. The present article addresses this concern by propagating uncertainties in atmospheric conditions, - namely turbulence intensity, wind shear and air density - wind rose and thrust curve forward to quantify the statistical uncertainty in AEP uplift estimations and by performing a sensitivity analysis to rank the significance of these uncertainties. For the Offshore Windpark Egmond aan Zee (OWEZ), the 95% confidence interval for the GCH is between 0.88% and 0.93%, while for the CC model this is between 1.08% and 1.14%. When compared with the deterministic AEP uplift of 0.97% for the GCH and 1.16% for the CC respectively, it is concluded that there is benefit from wake steering under input uncertainty for the OWEZ wind farm. Finally, for this case study the main driver of the variation in AEP uplift is the wind rose, with the other parameters having negligible effects.
