Reliability-based design optimisation framework for wind turbine towers

Shaikha Al-Sanad; Lin Wang; Jafarali Parol; Athanasios Kolios

doi:10.1016/j.renene.2020.12.022

Reliability-based design optimisation framework for wind turbine towers

Shaikha Al-Sanad, Lin Wang, Jafarali Parol, Athanasios Kolios

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Abstract

The current design of wind turbine (WT) towers is generally based on the partial safety factor (PSF) method, which treats uncertain variables deterministically and applies PSFs to account for uncertainties. This simplification in the design process leads to either over-engineered or under-engineered designs most of the time. In this study, a reliability-based design optimisation (RBDO) framework for WT towers is developed, accurately taking account of uncertainties in wind loads and material properties. A parametric finite element analysis (FEA) model for WT towers is developed, taking account of stochastic variables. After validation, it is then combined with response surface method and first order reliability method to develop a reliability assessment model. Five limit states are considered, i.e. ultimate, fatigue, buckling, modal frequency and tower top rotation. The reliability assessment model is further integrated with a genetic algorithm (GA) to develop a RBDO framework. The RBDO framework has been applied to a typical 2.0 MW onshore WT tower currently installed in a representative location in Middle East. The results demonstrate that the proposed RBDO framework can effectively and accurately achieve an optimal design of WT towers to meet target reliability.

Original language	English
Pages (from-to)	942-953
Number of pages	12
Journal	Renewable Energy
Volume	167
Early online date	8 Dec 2020
DOIs	https://doi.org/10.1016/j.renene.2020.12.022
Publication status	Published - Apr 2021

Bibliographical note

NOTICE: this is the author’s version of a work that was accepted for publication in Renewable Energy. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Renewable Energy, 167, (2021) DOI: 10.1016/j.renene.2020.12.022

© 2021, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/

Keywords

Finite element analysis
Genetic algorithm
Reliability-based design optimisation
Response surface method
Wind turbine
Wind turbine tower

ASJC Scopus subject areas

Renewable Energy, Sustainability and the Environment

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1016/j.renene.2020.12.022

Post-PrintAccepted author manuscript, 694 KBLicence: CC BY-NC-ND

Cite this

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title = "Reliability-based design optimisation framework for wind turbine towers",

abstract = "The current design of wind turbine (WT) towers is generally based on the partial safety factor (PSF) method, which treats uncertain variables deterministically and applies PSFs to account for uncertainties. This simplification in the design process leads to either over-engineered or under-engineered designs most of the time. In this study, a reliability-based design optimisation (RBDO) framework for WT towers is developed, accurately taking account of uncertainties in wind loads and material properties. A parametric finite element analysis (FEA) model for WT towers is developed, taking account of stochastic variables. After validation, it is then combined with response surface method and first order reliability method to develop a reliability assessment model. Five limit states are considered, i.e. ultimate, fatigue, buckling, modal frequency and tower top rotation. The reliability assessment model is further integrated with a genetic algorithm (GA) to develop a RBDO framework. The RBDO framework has been applied to a typical 2.0 MW onshore WT tower currently installed in a representative location in Middle East. The results demonstrate that the proposed RBDO framework can effectively and accurately achieve an optimal design of WT towers to meet target reliability.",

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author = "Shaikha Al-Sanad and Lin Wang and Jafarali Parol and Athanasios Kolios",

note = "NOTICE: this is the author{\textquoteright}s version of a work that was accepted for publication in Renewable Energy. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Renewable Energy, 167, (2021) DOI: 10.1016/j.renene.2020.12.022 {\textcopyright} 2021, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/ ",

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AU - Al-Sanad, Shaikha

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AU - Parol, Jafarali

AU - Kolios, Athanasios

N1 - NOTICE: this is the author’s version of a work that was accepted for publication in Renewable Energy. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Renewable Energy, 167, (2021) DOI: 10.1016/j.renene.2020.12.022 © 2021, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/

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N2 - The current design of wind turbine (WT) towers is generally based on the partial safety factor (PSF) method, which treats uncertain variables deterministically and applies PSFs to account for uncertainties. This simplification in the design process leads to either over-engineered or under-engineered designs most of the time. In this study, a reliability-based design optimisation (RBDO) framework for WT towers is developed, accurately taking account of uncertainties in wind loads and material properties. A parametric finite element analysis (FEA) model for WT towers is developed, taking account of stochastic variables. After validation, it is then combined with response surface method and first order reliability method to develop a reliability assessment model. Five limit states are considered, i.e. ultimate, fatigue, buckling, modal frequency and tower top rotation. The reliability assessment model is further integrated with a genetic algorithm (GA) to develop a RBDO framework. The RBDO framework has been applied to a typical 2.0 MW onshore WT tower currently installed in a representative location in Middle East. The results demonstrate that the proposed RBDO framework can effectively and accurately achieve an optimal design of WT towers to meet target reliability.

AB - The current design of wind turbine (WT) towers is generally based on the partial safety factor (PSF) method, which treats uncertain variables deterministically and applies PSFs to account for uncertainties. This simplification in the design process leads to either over-engineered or under-engineered designs most of the time. In this study, a reliability-based design optimisation (RBDO) framework for WT towers is developed, accurately taking account of uncertainties in wind loads and material properties. A parametric finite element analysis (FEA) model for WT towers is developed, taking account of stochastic variables. After validation, it is then combined with response surface method and first order reliability method to develop a reliability assessment model. Five limit states are considered, i.e. ultimate, fatigue, buckling, modal frequency and tower top rotation. The reliability assessment model is further integrated with a genetic algorithm (GA) to develop a RBDO framework. The RBDO framework has been applied to a typical 2.0 MW onshore WT tower currently installed in a representative location in Middle East. The results demonstrate that the proposed RBDO framework can effectively and accurately achieve an optimal design of WT towers to meet target reliability.

KW - Finite element analysis

KW - Genetic algorithm

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Reliability-based design optimisation framework for wind turbine towers

Abstract

Bibliographical note

Keywords

ASJC Scopus subject areas

UN SDGs

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