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Wind Energy Science The interactive open-access journal of the European Academy of Wind Energy
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h5-index value: 13
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Wind farm layout optimization is an essential part of wind farm design. In this paper, we present different methods to determine the number of turbines in a wind farm, as well as their placement. Also in this paper we explore the effect that the objective function has on the wind farm design, and found that wind farm layout is highly sensitive to the objective. The optimal number of turbines can vary greatly, from 15–54 for the cases in this paper, depending on the metric that is optimized.
Preprints
https://doi.org/10.5194/wes-2021-15
https://doi.org/10.5194/wes-2021-15

  18 Mar 2021

18 Mar 2021

Review status: a revised version of this preprint is currently under review for the journal WES.

Objective and Algorithm Considerations When Optimizing the Number and Placement of Turbines in a Wind Power Plant

Andrew P. J. Stanley, Owen Roberts, Jennifer King, and Christopher J. Bay Andrew P. J. Stanley et al.
  • National Renewable Energy Laboratory, National Wind Technology Center, Boulder, CO 80303 USA

Abstract. Optimizing turbine layout is a challenging problem that has been extensively researched in literature. However, optimizing the number of turbines within a given boundary has not been studied as extensively and is a difficult problem because it introduces discrete design variables and a discontinuous design space. An essential step in performing wind power plant layout optimization is to define the objective function, or value, that is used to express what is valuable to a wind power plant developer, such as annual energy production, cost of energy, or profit. In this paper, we demonstrate the importance of selecting the appropriate objective function when optimizing a wind power plant. We optimize several different wind power plants with different wind resources and boundary sizes. Results show that the optimal number of turbines varies drastically depending on the objective function. For a simple, one-dimensional, land-based scenario, we found that a wind power plant optimized for minimal cost of energy produced just 72 % of the profit as the wind power plant optimized for maximum profit, which corresponded to a loss of about $2 million each year. This paper also compares the performance of several different optimization algorithms, including a novel repeated-sweep algorithm that we developed. We found that the performance of each algorithm depended on the number of design variables in the problem as well as the objective function.

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
  • RC1: 'Comment on wes-2021-15', Anonymous Referee #1, 14 Apr 2021
  • RC2: 'Comment on wes-2021-15', Anonymous Referee #2, 11 May 2021
  • AC1: 'Response to reviewer 1', Andrew P. J. Stanley, 27 May 2021
  • AC2: 'Response to reviewer 2', Andrew P. J. Stanley, 27 May 2021

Andrew P. J. Stanley et al.

Andrew P. J. Stanley et al.

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Short summary
Wind farm layout optimization is an essential part of wind farm design. In this paper, we present different methods to determine the number of turbines in a wind farm, as well as their placement. Also in this paper we explore the effect that the objective function has on the wind farm design, and found that wind farm layout is highly sensitive to the objective. The optimal number of turbines can vary greatly, from 15–54 for the cases in this paper, depending on the metric that is optimized.
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