Reliability-based design optimisation framework for wind turbine towers. (April 2021)
- Record Type:
- Journal Article
- Title:
- Reliability-based design optimisation framework for wind turbine towers. (April 2021)
- Main Title:
- Reliability-based design optimisation framework for wind turbine towers
- Authors:
- Al-Sanad, Shaikha
Wang, Lin
Parol, Jafarali
Kolios, Athanasios - Abstract:
- 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. Highlights: A reliability-based design optimisation (RBDO) framework for wind turbine (WT) towers is developed. The RBDO framework has been applied to a typical 2 MW onshore WT tower. The proposedAbstract: 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. Highlights: A reliability-based design optimisation (RBDO) framework for wind turbine (WT) towers is developed. The RBDO framework has been applied to a typical 2 MW onshore WT tower. The proposed framework can achieve an optimal design of the WT tower to meet target reliability. The optimal design of the WT tower achieves a 15.1% mass reduction. … (more)
- Is Part Of:
- Renewable energy. Volume 167(2021)
- Journal:
- Renewable energy
- Issue:
- Volume 167(2021)
- Issue Display:
- Volume 167, Issue 2021 (2021)
- Year:
- 2021
- Volume:
- 167
- Issue:
- 2021
- Issue Sort Value:
- 2021-0167-2021-0000
- Page Start:
- 942
- Page End:
- 953
- Publication Date:
- 2021-04
- Subjects:
- Wind turbine -- Wind turbine tower -- Reliability-based design optimisation -- Finite element analysis -- Genetic algorithm -- Response surface method
Renewable energy sources -- Periodicals
Power resources -- Periodicals
Énergies renouvelables -- Périodiques
Ressources énergétiques -- Périodiques
333.794 - Journal URLs:
- http://www.sciencedirect.com/science/journal/09601481 ↗
http://www.elsevier.com/journals ↗
http://www.journals.elsevier.com/renewable-energy/ ↗ - DOI:
- 10.1016/j.renene.2020.12.022 ↗
- Languages:
- English
- ISSNs:
- 0960-1481
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 7364.187000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 15498.xml