09 Jan 2023
 | 09 Jan 2023
Status: this preprint is currently under review for the journal WES.

Enabling Control Co-Design of the Next Generation of Wind Plants

Andrew P. J. Stanley, Christopher J. Bay, and Paul Fleming

Abstract. Layout design and wake steering through wind plant control are each important and complex components in the design and operation of modern wind plants. They are currently optimized separately, but as more and more wind plants implement wake steering as their primary form of operation, there are increasing needs from industry and regulating bodies to combine the layout and control optimization in a co-design process. However, combining these two optimization problems is currently infeasible due to the excessive number of design variables and the very large solution space. In this paper we present a revolutionary method that enables the coupled optimization of wind plant layout and wake steering with no additional computational expense than a traditional layout optimization. This is accomplished through the development of a geometric relationship between turbines to find an approximate optimal yaw angle, bypassing the need for either a nested or coupled wind plant control optimization. The method we present in this paper provides a significant and immediate improvement to wind plant design by enabling the co-design of turbine layout and yaw control for wake steering. A small co-designed plant shown in this paper produces 0.8 % more energy than its sequentially designed counterpart, and we expect larger comparative gains for larger plants with more turbines. This additional energy production comes with no additional infrastructure, turbine hardware, or control software; it is a free consequence of optimizing the turbine layout and yaw control together, resulting in millions of dollars of additional revenue for the wind plants of the future.

Andrew P. J. Stanley et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • CC1: 'Comment on wes-2023-1', Adam Stock, 15 Mar 2023
    • AC1: 'Reply on CC1', Andrew P.J. Stanley, 18 May 2023
  • RC1: 'Comment on wes-2023-1', Anonymous Referee #1, 02 Apr 2023
    • AC2: 'Reply on RC1', Andrew P.J. Stanley, 18 May 2023
  • RC2: 'Comment on wes-2023-1', Sebastian Sanchez Perez-Moreno, 04 Apr 2023
    • AC3: 'Reply on RC2', Andrew P.J. Stanley, 18 May 2023

Andrew P. J. Stanley et al.

Andrew P. J. Stanley et al.


Total article views: 496 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
314 163 19 496 3 1
  • HTML: 314
  • PDF: 163
  • XML: 19
  • Total: 496
  • BibTeX: 3
  • EndNote: 1
Views and downloads (calculated since 09 Jan 2023)
Cumulative views and downloads (calculated since 09 Jan 2023)

Viewed (geographical distribution)

Total article views: 479 (including HTML, PDF, and XML) Thereof 479 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
Latest update: 27 May 2023
Short summary
Better wind farms can be built by simultaneously optimizing turbine locations and control, which is currently impossible or extremely challenging because of the size of the problem. The authors present a method to determine optimal wind farm control as function of the turbine locations, which enables turbine layout and control to be optimized together by drastically reducing the size of the problem. In an example, a wind farm's performance improves by 0.8 % when optimized with the new method.