LAPSE:2023.33332
Published Article
LAPSE:2023.33332
General Methodology for the Identification of Reduced Dynamic Models of Barge-Type Floating Wind Turbines
Daniel Villoslada, Matilde Santos, María Tomás-Rodríguez
April 21, 2023
Floating offshore wind turbines (FOWT) are designed to overcome some of the limitations of offshore bottom-fixed ones. The development of computational models to simulate the behavior of the structure and the turbine is key to understanding the wind energy system and demonstrating its feasibility. In this work, a general methodology for the identification of reduced dynamic models of barge-type FOWTs is presented. The method is described together with an example of the development of a dynamic model of a 5 MW floating offshore wind turbine. The novelty of the proposed identification methodology lies in the iterative loop relationship between the identification and validation processes. Diversified data sets are used to select the best-fitting identified parameters by cross evaluation of every set among all validating conditions. The data set is generated for different initial FOWT operating conditions. Indeed, an optimal initial condition for platform pitch was found to be far enough from the system at rest to allow the dynamics to be well characterized but not so far that the unmodeled system nonlinearities were so large that they affected significantly the accuracy of the model. The model has been successfully applied to structural control research to reduce fatigue on a barge-type FOWT.
Keywords
barge-type floating wind turbine, dynamic control-oriented model, identification, offshore wind energy, reduced DOF model
Suggested Citation
Villoslada D, Santos M, Tomás-Rodríguez M. General Methodology for the Identification of Reduced Dynamic Models of Barge-Type Floating Wind Turbines. (2023). LAPSE:2023.33332
Author Affiliations
Villoslada D: Computer Sciences Faculty, University Complutense of Madrid, 28040 Madrid, Spain
Santos M: Institute of Knowledge Technology, University Complutense of Madrid, 28040 Madrid, Spain [ORCID]
Tomás-Rodríguez M: Department of Mechanical Engineering and Aeronautics, School of Mathematics, Computer Science and Engineering, City University of London, London EC1V 0HB, UK
Journal Name
Energies
Volume
14
Issue
13
First Page
3902
Year
2021
Publication Date
2021-06-29
Published Version
ISSN
1996-1073
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PII: en14133902, Publication Type: Journal Article
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LAPSE:2023.33332
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doi:10.3390/en14133902
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Apr 21, 2023
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