Posters

Abstract

Wind flow and wake models typically account for a large part of the uncertainty of any energy yield assessment. It is not uncommon for atmospheric stability conditions not to be considered throughout these assessments. In this work, we aim at illustrating the impact of the inclusion of stability within wind flow and wake models on energy yield and its uncertainty. To this end, two sites with concurrent data from two and four pre-construction met masts respectively are considered, both of which are located in complex terrain. Three flow models are run to simulate the flow conditions across the sites: the WAsP linear flow model, the Meteodyn RANS CFD model, and the WRF mesoscale model. WAsP and Meteodyn are initially setup to represent neutral flow conditions. The performance of the three models is compared in terms of mean wind speed, directional wind speed, and wind power. We illustrate how these metrics can be misleading, as a low bias on wind speed does not necessarily guarantee a low bias on wind power. Stability metrics (Monin-Obukhov Length, Bulk Richardson, Pasquill) are derived from on-site weather conditions and from ERA5 re-analysis data. We illustrate how sensitive the assessment of stability is to the choice of metric selected for the analysis. These metrics are then used together with WAsP and Meteodyn in non-neutral mode by accounting for site-specific atmospheric stability classes. The performance of the three models is again compared as above, illustrating the high sensitivity of bias on wind speed to choices made regarding atmospheric stability. In particular, the sensitivity of choices made to link stability measurements and microscale #_msocom_2 wind flow models is discussed. For one of the two sites, SCADA data is available. The dataset is first filtered out in order to be useable for comparison with wind flow and wake models. Standard engineering wake models (NO Jensen and Eddy-viscosity) are superimposed to the background wind flow derived from the three flow models. The wake decay constant of the NO Jensen model is computed in various ways, making use of measured turbulence intensity as well as of stability metrics. Results are finally compared to SCADA data. We conclude by illustrating how choices made regarding the inclusion of atmospheric stability within energy yield assessments impact P50, P90 and ultimately project value.