Preprints
https://doi.org/10.5194/wes-2021-152
https://doi.org/10.5194/wes-2021-152
 
18 Jan 2022
18 Jan 2022
Status: this preprint is currently under review for the journal WES.

Multifidelity Multiobjective Optimization for Wake Steering Strategies

Julian Quick1,2, Ryan N. King2, Garrett Barter2, and Peter E. Hamlington1 Julian Quick et al.
  • 1University of Colorado, Boulder, CO, USA
  • 2National Renewable Energy Laboratory, Golden, CO, USA

Abstract. Wake steering is an emerging wind power plant control strategy where upstream turbines are intentionally yawed out of perpendicular alignment with the incoming wind, thereby “steering” wakes away from downstream turbines. However, trade-offs between the gains in power production and fatigue loads induced by this control strategy are the subject of continuing investigation. In this study, we present a multifidelity multiobjective optimization approach for exploring the Pareto front of trade-offs between power and loading during wake steering. An unsteady large-eddy simulation is used as the high-fidelity model, where an actuator line representation is used to model wind turbine blades, and a rainflow-counting algorithm is used to compute damage equivalent loads. A coarser simulation with a simpler loads model is employed as a supplementary low-fidelity model. A multifidelity Bayesian optimization is performed to iteratively learn both a surrogate of the low-fidelity model and an additive discrepancy function, which maps the low-fidelity model to the high-fidelity model. Each optimization uses the expected hypervolume improvement acquisition function, weighted by the total cost of a proposed model evaluation in the multifidelity case. The multifidelity approach is able to capture the logit function shape of the Pareto frontier at a computational cost that is only 30 % of the single fidelity approach. Additionally, we provide physical insights into the vortical structures in the wake that contribute to the Pareto front shape.

Julian Quick et al.

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-2021-152', Anonymous Referee #1, 15 Feb 2022
  • RC2: 'Comment on wes-2021-152', Anonymous Referee #2, 22 Feb 2022

Julian Quick et al.

Julian Quick et al.

Viewed

Total article views: 332 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
230 91 11 332 1 2
  • HTML: 230
  • PDF: 91
  • XML: 11
  • Total: 332
  • BibTeX: 1
  • EndNote: 2
Views and downloads (calculated since 18 Jan 2022)
Cumulative views and downloads (calculated since 18 Jan 2022)

Viewed (geographical distribution)

Total article views: 322 (including HTML, PDF, and XML) Thereof 322 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 20 May 2022
Download
Short summary
Wake steering is an emerging wind power plant control strategy where upstream turbines are intentionally yawed out of alignment with the incoming wind, thereby “steering” wakes away from downstream turbines. Trade-offs between the gains in power production and fatigue loads induced by this control strategy are the subject of continuing investigation. In this study, we present an optimization approach for efficiently exploring the trade-offs between power and loading during wake steering.