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Optimization of a low speed wind turbine using support vector regression

Thesis (MScEng (Mechanical and Mechatronic Engineering))--University of Stellenbosch, 2009.

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Main Author: Wise, John Nathaniel
Other Authors: Venter, Gerhard
Format: Thesis
Language:English
Published: Stellenbosch : University of Stellenbosch 2009
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access_status_str Open Access
author Wise, John Nathaniel
author2 Venter, Gerhard
author_browse Venter, Gerhard
Wise, John Nathaniel
author_facet Venter, Gerhard
Wise, John Nathaniel
author_sort Wise, John Nathaniel
collection Thesis
dc_rights_str_mv University of Stellenbosch
description Thesis (MScEng (Mechanical and Mechatronic Engineering))--University of Stellenbosch, 2009.
format Thesis
id oai:scholar.sun.ac.za:10019.1/2737
institution Stellenbosch University (South Africa)
language English
last_indexed 2026-06-10T12:46:52.985Z
license_str Other — see source repository
provenance_str_mv Harvested via OAI-PMH from SUNScholar — Stellenbosch University Repository
publishDate 2009
publishDateRange 2009
publishDateSort 2009
publisher Stellenbosch : University of Stellenbosch
publisherStr Stellenbosch : University of Stellenbosch
record_format dspace
source_str SUNScholar — Stellenbosch University Repository
spelling oai:scholar.sun.ac.za:10019.1/2737 Optimization of a low speed wind turbine using support vector regression Wise, John Nathaniel Venter, Gerhard University of Stellenbosch. Faculty of Engineering. Dept. of Mechanical and Mechatronic Engineering. Dissertations -- Mechanical engineering Theses -- Mechanical engineering Wind turbines -- Aerodynamics Aerofoils Mechanical and Mechatronic Engineering Thesis (MScEng (Mechanical and Mechatronic Engineering))--University of Stellenbosch, 2009. NUMERICAL design optimization provides a powerful tool that assists designers in improving their products. Design optimization automatically modifies important design parameters to obtain the best product that satisfies all the design requirements. This thesis explores the use of Support Vector Regression (SVR) and demonstrates its usefulness in the numerical optimization of a low-speed wind turbine for the power coe cient, Cp. The optimization design problem is the three-dimensional optimization of a wind turbine blade by making use of four two-dimensional radial stations. The candidate airfoils at these stations are selected from the 4-digit NACA range. A metamodel of the lift and drag coe cients of the NACA 4-digit series is created with SVR by using training points evaluated with XFOIL software. These SVR approximations are used in conjunction with the Blade Element Momentum theory to calculate and optimize the Cp value for the entire blade. The high accuracy attained with the SVR metamodels makes it a viable alternative to using XFOIL directly, as it has the advantages of being faster and easier to couple with the optimizer. The technique developed allows the optimization procedure the freedom to select profiles, angles of attack and chord length from the 4-digit NACA series to find an optimal Cp value. As a result of every radial blade station consisting of a NACA 4-digit series, the same lift and drag metamodels are used for each station. This technique also makes it simple to evaluate the entire blade as one set of design variables. The thesis contains a detailed description of the design and optimization problem, the implementation of the SVR algorithm, the creation of the lift and drag metamodels with SVR and an alternative methodology, the BEM theory and a summary of the results. 2009-02-27T06:11:54Z 2010-06-01T08:57:03Z 2009-02-27T06:11:54Z 2010-06-01T08:57:03Z 2009-03 Thesis http://hdl.handle.net/10019.1/2737 en University of Stellenbosch application/pdf Stellenbosch : University of Stellenbosch
spellingShingle Dissertations -- Mechanical engineering
Theses -- Mechanical engineering
Wind turbines -- Aerodynamics
Aerofoils
Mechanical and Mechatronic Engineering
Wise, John Nathaniel
Optimization of a low speed wind turbine using support vector regression
title Optimization of a low speed wind turbine using support vector regression
title_full Optimization of a low speed wind turbine using support vector regression
title_fullStr Optimization of a low speed wind turbine using support vector regression
title_full_unstemmed Optimization of a low speed wind turbine using support vector regression
title_short Optimization of a low speed wind turbine using support vector regression
title_sort optimization of a low speed wind turbine using support vector regression
topic Dissertations -- Mechanical engineering
Theses -- Mechanical engineering
Wind turbines -- Aerodynamics
Aerofoils
Mechanical and Mechatronic Engineering
url http://hdl.handle.net/10019.1/2737
work_keys_str_mv AT wisejohnnathaniel optimizationofalowspeedwindturbineusingsupportvectorregression