Wind farm structural response and wake dynamics for an evolving stable boundary layer: computational and experimental comparisons

Author:

Shaler KelseyORCID,Quon EliotORCID,Ivanov Hristo,Jonkman JasonORCID

Abstract

Abstract. The wind turbine design process requires performing thousands of simulations for a wide range of inflow and control conditions, which necessitates computationally efficient yet time-accurate models, especially when considering wind farm settings. To this end, FAST.Farm is a dynamic-wake-meandering-based mid-fidelity engineering tool developed by the National Renewable Energy Laboratory targeted at accurately and efficiently predicting wind turbine power production and structural loading in wind farm settings, including wake interactions between turbines. This work is an extension of a study that addressed constructing a diurnal cycle evolution based on experimental data (Quon, 2024). Here, this inflow is used to validate the turbine structural and wake-meandering response between experimental data, FAST.Farm simulation results, and high-fidelity large-eddy simulation results from the coupled Simulator fOr Wind Farm Applications (SOWFA)–OpenFAST tool. The validation occurs within the nocturnal stable boundary layer when corresponding meteorological and turbine data are available. To this end, we compared the load results from FAST.Farm and SOWFA–OpenFAST to multi-turbine measurements from a subset of a full-scale wind farm. Computational predictions of blade-root and tower-base bending loads are compared to 10 min statistics of strain gauge measurements during 3.5 h of the evolving stable boundary layer, generally with good agreement. This time period coincided with an active wake-steering campaign of an upstream turbine, resulting in time-varying yaw positions of all turbines. Wake meandering was also compared between the computational solutions, generally with excellent agreement. Simulations were based on a high-fidelity precursor constructed from inflow measurements and using state-of-the-art mesoscale-to-microscale coupling.

Funder

National Renewable Energy Laboratory

Publisher

Copernicus GmbH

Reference18 articles.

1. Asmuth, H., Navarro Diaz, G. P., Madsen, H. A., Branlard, E., Myer Forsting, A. R., Nilsson, K., Jonkman, J., and Ivanell, S.: Wind Turbine Response in Waked Inflow: A Modelling Benchmark Against Full-Scale Measurements, Renew. Energy, 191, 868–887, https://doi.org/10.1016/j.renene.2022.04.047, 2022. a

2. Doubrawa, P., Quon, E. W., Martinez-Tossas, L. A., Shaler, K., Debnath, M., Hamilton, N., Herges, T. G., Maniaci, D., Kelley, C. L., Hsieh, A. S., Blaylock, M. L., van der Laan, P., Andersen, S. J., Krueger, S., Cathelain, M., Schlez, W., Jonkman, J., Branlard, E., Steinfield, G., Schmidt, S., Blondel, F., Lukassen. L. J., and Moriarty, P.: Multi-Model Validation of Single Wakes in Neutral and Stratified Atmospheric Conditions, Wind Energy, 23, 2027–2055, https://doi.org/10.1002/(ISSN)1099-1824, 2020. a, b, c, d

3. Fleming, P., King, J., Dykes, K., Simley, E., Roadman, J., Scholbrock, A., Murphy, P., Lundquist, J. K., Moriarty, P., Fleming, K., van Dam, J., Bay, C., Mudafort, R., Lopez, H., Skopek, J., Scott, M., Ryan, B., Guernsey, C., and Brake, D.: Initial results from a field campaign of wake steering applied at a commercial wind farm – Part 1, Wind Energ. Sci., 4, 273–285, https://doi.org/10.5194/wes-4-273-2019, 2019. a

4. Fleming, P., King, J., Simley, E., Roadman, J., Scholbrock, A., Murphy, P., Lundquist, J. K., Moriarty, P., Fleming, K., van Dam, J., Bay, C., Mudafort, R., Jager, D., Skopek, J., Scott, M., Ryan, B., Guernsey, C., and Brake, D.: Continued results from a field campaign of wake steering applied at a commercial wind farm – Part 2, Wind Energ. Sci., 5, 945–958, https://doi.org/10.5194/wes-5-945-2020, 2020. a, b

5. Ivanov, H., Dana, S., and Doubrawa, P.: Loads Response That is Due to Wake Steering on a Pair of Utility-Scale Wind Turbines, Tech. Rep. NREL/TP-5000-79187, National Renewable Energy Laboratory, Golden, CO, https://www.nrel.gov/docs/fy21osti/79187.pdf (last access: 15 June 2024), 2021. a

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