Assessing the Progression of Wind Turbine Energy Yield Losses Due to Blade Erosion by Resolving Damage Geometries from Lab Tests and Field Observations

Castorrini, Alessio; Ortolani, Andrea; Campobasso, M. Sergio

doi:10.2139/ssrn.4385156

Cited by 1 publication

(6 citation statements)

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“…The model requires defining the sand grain roughness K s value for the rough-wall boundary conditions, and a measure of the actual roughness height K for the rough-wall transition model. The sand grain roughness is used in an the automatic wall treatment based on rough wall functions (details in [19,8,20,6]). The roughness height parameter K is used to define a modification term in the γ-Re θ SST transition model.…”

Section: Computational Aerodynamics Modelmentioning

confidence: 99%

“…The roughness height parameter K is used to define a modification term in the γ-Re θ SST transition model. In particular, the Re θ field is modified to account for the increase of the BL momentum thickness due to the unresolved roughness [19,8,6]. Figure 2a shows the LE mesh for a case with groove damage of positive curvilinear extension on both suction side and pressure side.…”

Section: Computational Aerodynamics Modelmentioning

confidence: 99%

“…In [5], AEP losses were found to vary from 1% for LEE made of pits and gauges to 6% for LEE due to extended loss of coating. In [6], a field recorded damage geometry was used to define the CFD model for different possible damage severity states. The study 2 shows that up to 1% of AEP can be lost when LEE trips the boundary layer (BL) laminar-toturbulent transition at the LE along a significant portion of the blade, whereas the presence of severe damages can further spoil the blade performance, from 1 to 3.5%, depending on the damage geometry and location.…”

Section: Introductionmentioning

confidence: 99%

“…A fundamental information required to generate a reliable BEMT model of the damaged blade is the accurate estimate of its airfoils' lift (c l ) and drag (c d ) coefficients for each LEE damage considered. The effects of LEE on c l and c d have been extensively investigated through wind tunnel tests [3,7] and numerical simulation [8,6], showing that both small-scale surface roughness and large-scale surface alterations have a significant effect on the blade performance.…”

Section: Introductionmentioning

confidence: 99%

“…The damage scale separation is accounted for in the definition of the CFD model. Similarly to [6], a fully turbulent approach and damage resolving CFD mesh is used for airfoils with grooves, assuming the BL laminar-to-turbulent transition to always occur at the LE. For small-amplitude roughness, the BL transition location is crucial for accurately predicting the force coefficients; hence, a transitional RANS model is used to simulate the nominal airfoil geometry with rough wall.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Opensource machine learning metamodels for assessing blade performance impairment due to general leading edge degradation

Castorrini,

Ortolani,

Minisci

et al. 2024

J. Phys.: Conf. Ser.

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Blades leading edge erosion can significantly reduce annual energy production of wind turbines. Accurate estimates of the resulting blade performance impairment are paramount to predict the resulting energy losses and enable cost-informed decisions on optimal maintenance and operational strategies, maximizing energy production and reducing maintenance costs. Computational Fluid Dynamics (CFD) is a robust approach for predicting the performance losses due to LEE. However, the impact of the damage on blade aerodynamics varies depending on damage pattern, extent and location. Therefore, direct CFD simulation of a sufficiently general set of damaged blades is computationally not viable in industrial applications, since the energy loss assessment needs to be performed for hundreds of turbines at many times of the wind farm operation. To address this issue, previous studies showed how CFD can be used to train machine learning metamodels of the perfomance of damaged blade sections, enabling the definition of multi-fidelity energy loss prediction systems. This study presents improved metamodels, using validated CFD to generate training datasets that cover a more general and wider range of erosion patterns, from low-amplitude roughness to severe grooves. In order to provide the industry with additional erosion geometry-linked tools for estimating energy yield losses, and foster further research and development in this area, the developed meta-models have been made available online with unrestricted access.

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Section: Computational Aerodynamics Modelmentioning

confidence: 99%

Section: Computational Aerodynamics Modelmentioning

confidence: 99%