Preprints
https://doi.org/10.5194/wes-2022-44
https://doi.org/10.5194/wes-2022-44
 
27 Jun 2022
27 Jun 2022
Status: this preprint is currently under review for the journal WES.

Brief communication: A momentum-conserving superposition method applied to the super-Gaussian wind turbine wake model

Frédéric Blondel Frédéric Blondel
  • 1-4 Av. du Bois Préau, 92852 Rueil-Malmaison

Abstract. Accurate wind farm flow predictions based on analytical wake models are crucial for wind farm design and layout optimisation. In this regard, wake superposition methods play a key role and remain a substantial source of uncertainty. Recently, new models based on mass and momentum conservation have been proposed in the literature. In the present work, such methods are extended to the superposition of super-Gaussian type velocity deficit models, allowing the full wake velocity deficit estimation and design of closely packed wind farms.

Frédéric Blondel

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on wes-2022-44', Anonymous Referee #1, 04 Aug 2022
  • RC2: 'Comment on wes-2022-44', Anonymous Referee #2, 09 Aug 2022

Frédéric Blondel

Frédéric Blondel

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Short summary
Accurate wind farm flow predictions based on analytical wake models are crucial for wind farm design and layout optimisation. Wake superposition methods play a key role and remain a substantial source of uncertainty. In the present work, a momentum-conserving superposition method is extended to the superposition of super-Gaussian type velocity deficit models, allowing the full wake velocity deficit estimation and design of closely packed wind farms.