Reliability-based design optimisation framework for wind turbine towers

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

Research output: Contribution to journalArticlepeer-review

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 languageEnglish
Pages (from-to)942-953
Number of pages12
JournalRenewable Energy
Volume167
Early online date8 Dec 2020
DOIs
Publication statusPublished - 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

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