Modelling Uncertainty in t-RANS Simulations of Thermally Stratified Forest Canopy Flows for Wind Energy Studies

Cian Desmond; Simon Watson; Christiane Montavon; Jimmy Murphy

doi:10.3390/en11071703

Modelling Uncertainty in t-RANS Simulations of Thermally Stratified Forest Canopy Flows for Wind Energy Studies

Energies ◽

10.3390/en11071703 ◽

2018 ◽

Vol 11 (7) ◽

pp. 1703 ◽

Cited By ~ 1

Author(s):

Cian Desmond ◽

Simon Watson ◽

Christiane Montavon ◽

Jimmy Murphy

Keyword(s):

Wind Energy ◽

Forest Canopy ◽

Modelling Uncertainty ◽

Canopy Flows ◽

Rans Simulations

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Comparing and validating intra-farm and farm-to-farm wakes across different mesoscale and high-resolution wake models

10.5194/wes-2021-106 ◽

2021 ◽

Author(s):

Jana Fischereit ◽

Kurt Schaldemose Hansen ◽

Xiaoli Guo Larsén ◽

Maarten Paul van der Laan ◽

Pierre-Elouan Réthoré ◽

...

Keyword(s):

High Resolution ◽

Wind Energy ◽

Wind Farm ◽

Wind Farms ◽

Offshore Wind ◽

Wake Effect ◽

Disk Model ◽

Computational Costs ◽

Rans Simulations ◽

Wind Resource

Abstract. Numerical wind resource modelling across scales from mesoscale to turbine scale is of increasing interest due to the expansion of offshore wind energy. Offshore, wind farm wakes can last several tens kilometres downstream and thus affect the wind resources of a large area. So far, scale-specific models have been developed and it remains unclear, how well the different model types can represent intra-farm wakes, farm-to-farm wakes as well as the wake recovery behind a farm. Thus, in the present analysis the simulation of a set of wind farm models of different complexity, fidelity, scale and computational costs are compared among each other and with SCADA data. In particular, two mesoscale wind farm parameterizations implemented in the mesoscale Weather Research and Forecasting model (WRF), the Explicit Wake Parameterization (EWP) and the Wind Farm Parameterization (FIT), two different high-resolution RANS simulations using PyWakeEllipSys equipped with an actuator disk model, and three rapid engineering wake models from the PyWake suite are selected. The models are applied to the Nysted and Rødsand II wind farms, which are located in the Fehmarn Belt in the Baltic Sea. Based on the performed simulations, we can conclude that average intra-farm variability can be captured reasonable well with WRF+FIT using a resolution of 2 km, a typical resolution of mesoscale models for wind energy applications, while WRF+EWP underestimates wind speed deficits. However, both parameterizations can be used to estimate median wind resource reduction caused by an upstream farm. All considered engineering wake models from the PyWake suite simulate intra-farm wakes comparable to the high fidelity RANS simulations. However, they considerably underestimate the farm wake effect of an upstream farm although with different magnitudes. Overall, the higher computational costs of PyWakeEllipSys and WRF compared to PyWake pay off in terms of accuracy for situations when farm-to-farm wakes are important.

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Numerical simulation of non-neutral forest canopy flows at a site in North-Eastern France

10.5194/wes-2017-34 ◽

2017 ◽

Author(s):

Cian J. Desmond ◽

Simon J. Watson ◽

Christiane Montavon ◽

Jimmy Murphy

Keyword(s):

Fluid Dynamics ◽

Numerical Simulation ◽

Computational Fluid Dynamics ◽

Forest Canopy ◽

State Of The Art ◽

Canopy Density ◽

North Eastern ◽

Canopy Flows ◽

A Site ◽

Neutral Conditions

Abstract. The flow over densely forested terrain under neutral and non-neutral conditions is considered using commercially available Computational Fluid Dynamics software. Results are validated against data from a site in North-Eastern France. It is shown that the effects of both neutral and stable atmospheric stratifications can be modelled numerically using state of the art methodologies whilst unstable stratifications are more difficult to simulate accurately. The sensitivity of the numerical model to parameters such as canopy height, canopy density and the turbulence modelling constant Cμ is also assessed.

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