Preprints
https://doi.org/10.5194/wes-2023-14
https://doi.org/10.5194/wes-2023-14
02 Mar 2023
 | 02 Mar 2023
Status: this preprint is currently under review for the journal WES.

Extending the Dynamic Wake Meandering Model in HAWC2Farm: Lillgrund Wind Farm Case Study and Validation

Jaime Liew, Tuhfe Göçmen, Alan W. H. Lio, and Gunner Chr. Larsen

Abstract. With the increasing growth of wind farm installations, the impact of wake effects from wind turbines on power output, structural loads, and revenue has become a major concern. Hence, there is a need for precise simulation tools to facilitate efficient and cost-effective design and operation of wind farms. To address this need, we present HAWC2Farm, a dynamic and versatile aeroelastic wind farm simulation methodology that combines state-of-the-art engineering models to accurately capture the complex physical phenomena in wind farms. HAWC2Farm models each turbine in a wind farm using the aeroelastic turbine simulator, HAWC2, while sharing a large, high-resolution turbulence box to model atmospheric flow field effects at the farm level, and a modified Dynamic Wake Meandering (DWM) model for capturing wake interactions. The method is computationally efficient and provides valuable insights for wind farm design. It is validated using time series field measurements from the Lillgrund wind farm, including scenarios with yaw steering and a turbine shutdown. HAWC2Farm addresses the challenges of modelling the complex dynamics in wind farms, enabling more accurate, informed and cost-effective design and operation.

Jaime Liew et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse

Jaime Liew et al.

Jaime Liew et al.

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Short summary
We present recent research on dynamically modelling wind farm wakes, and integrating these enhancements into the wind farm simulator, HAWC2Farm. The simulation methodology is showcased by recreating dynamic scenarios observed in the Lillgrund offshore wind farm. We successfully recreate scenarios with turning winds, turbine shut down events, and wake deflection events. The research provides opportunities to better identify wake interactions in wind farms, allowing for more reliable designs.