Wind power generation prediction in a complex site by comparing different numerical tools

This paper focuses on the estimation of annual energy production (AEP) by simulating the flowfield on a complex terrain located in the northeast region of Brazil using different numerical approaches: CFD RANS with k-epsilon and k-omega turbulence models (WindSim), simple mass-conserving (WindMap), and refined mesoscale (SiteWind). The last two are run through OpenWind software. Wind observations from five meteorological masts are used to adjust the models. Optimal layouts for a hypothetical wind farm with 50 wind turbines are obtained over each of the four wind fields to predict the power generation. As non-negligible differences are found on the spatial distri-bution of the winds simulated by the different models, the layouts are also substantially different. The AEP is calculated to compare scenarios varying the layouts over the wind fields. The distinct micrositing generate differences of up to 13 % on AEP prediction, which could mean the impact of an improper siting on the wind farm profitability. It is not plausible to categorically claim the superiority of accuracy of one model over the others. Nonetheless, the observed data provide an indicative that the refined mesoscale model was able to better capture the wind acceleration in the western region of the studied site.

Automated summary

This paper focuses on estimating annual energy production (AEP) on a complex terrain in northeast Brazil using various numerical approaches. Different models are used to simulate wind fields, with optimal layouts for a hypothetical wind farm obtained to predict power generation. The study found significant differences in wind distribution among the models, leading to varying layouts and up to 13% differences in AEP predictions.