LAPSE:2023.29615
Published Article
LAPSE:2023.29615
Optimal Pitch Angle Strategy for Energy Maximization in Offshore Wind Farms Considering Gaussian Wake Model
April 13, 2023
This paper presents a new approach based on the optimization of the blade pitching strategy of offshore wind turbines in order to maximize the global energy output considering the Gaussian wake model and including the effect of added turbulence. A genetic algorithm is proposed as an optimization tool in the process of finding the optimal setting of the wind turbines, which aims to determine the individual pitch of each turbine so that the overall losses due to the wake effect are minimised. The integration of the Gaussian model, including the added turbulence effect, for the evaluation of the wakes provides a step forward in the development of strategies for optimal operation of offshore wind farms, as it is one of the state-of-the-art analytical wake models that allow the evaluation of the energy output of the project in a more reliable way. The proposed methodology has been tested through the execution of a set of test cases that show the ability of the proposed tool to maximize the energy production of offshore wind farms, as well as highlights the importance of considering the effect of added turbulence in the evaluation of the wake.
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Keywords
Genetic Algorithm, offshore wind farm, wake effect, wind energy, wind farm, wind farm operation
Subject
Suggested Citation
Serrano González J, López B, Draper M. Optimal Pitch Angle Strategy for Energy Maximization in Offshore Wind Farms Considering Gaussian Wake Model. (2023). LAPSE:2023.29615
Author Affiliations
Serrano González J: Department of Electrical Engineering, University of Seville, 41092 Seville, Spain [ORCID]
López B: IMFIA, Facultad de Ingeniería, Universidad de la República, Montevideo 11200, Uruguay
Draper M: IMFIA, Facultad de Ingeniería, Universidad de la República, Montevideo 11200, Uruguay
López B: IMFIA, Facultad de Ingeniería, Universidad de la República, Montevideo 11200, Uruguay
Draper M: IMFIA, Facultad de Ingeniería, Universidad de la República, Montevideo 11200, Uruguay
Journal Name
Energies
Volume
14
Issue
4
First Page
938
Year
2021
Publication Date
2021-02-10
ISSN
1996-1073
Version Comments
Original Submission
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PII: en14040938, Publication Type: Journal Article
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LAPSE:2023.29615
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https://doi.org/10.3390/en14040938
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Apr 13, 2023
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