Multi-objective optimization design of small wind turbine blade
Pages 287 - 290
Abstract
The multi - objective optimization design of small wind turbine blade is studied. Based on the theory of blade element - momentum and cantilever beam, combined with genetic algorithm, the mathematical model of optimal design of blade structure was established by taking the chord length, twist Angle and thickness of blade sections as design variables, the shape and stress as constraints, the lightweight of blade and the maximization of wind energy capture as objective functions. Taking a 10kW wind turbine blade as an example, the relationship between the three shape parameters of the blade before and after optimization and the impeller quality and wind energy capture of the wind turbine was analyzed. The calculation and analysis show that the optimized blade can not only improve the utilization coefficient of wind energy, but also reduce the mass line density of the blade section and realize the lightweight.
References
[1]
Pengqiuming. Simulation and optimization the Aerodymic Performance of 1 DkW Wind Turbine Biade Airfoi[D]. Xiangtan University,2011.
[2]
GUO Xiao-feng,Shu-feng. A Coupling Optimization Design of Aerodynamic Shape and Operating Characteristics of Wind Turbine Blades[J]. Machinery Design & Manufacture. 2019, 3:204--207.
[3]
Long Chen1, Yidu Zhang and Zhanqiang Liu. Optimization design and simulationanalysis of composite material anti-/deicing component for wind turbine blade[J]. Earth and Environmental Science. 227 (2019) 032035.
[4]
WANG Hao, LU Yang, ZHOU Huan, HAN Chunhui. Optimization Design of Horizontal Axis Wind Turbine Blade Based on Wilson Method and Genetic Algorithm[J]. Journal of Shanghai University of Electric Power. 2018,04: 1006--4729.
[5]
WANG Quan, HONG Xing, YANG Jianzhong2 WANG Jun, SUN Jinfeng, QIN Zhengzheng. Aerodynamic Optimal Design of Low Noise Wind Turbine Blades[J]. CHINA MECHANICAL ENGINEERING.2018,7(13):1574--1579.
[6]
L Tenghiri, Y Khalil, F Abdi, A Bentamy. Optimum design of a small wind turbine blade for maximum power production[C]. Earth and Environmental Science.2018,161: 1088/1755--1315.
[7]
Zhang Youyou Zheng Yujiao Chen Yuyan Sun Meimei Tang Jiamian Zhu Jie. Structural topology optimization design of wind turbine blade[J]. SHANXI ARCHITTECTURE. 2017,43(15):203--204.
[8]
Ding Tao, Liu Jiang, Fang Lumeng. OPTIMIZATION DESIGN OF SAVONIUS WIND TURBINE BLADE BASED ON MULTIPLE BEZIER CURVE[J]. ACTA ENERGIAE SOLARIS SINICA.2017,38(4):959--965.
[9]
WANG Hao-yu ZHU Fa-wen LIU Yang-hua QI Min GU Ming-fei ZHENG Mei-yin. Optimization Design of Variable-speed Variable-pitch Wind Turbine Blade in Low Wind Speed Condition[J]. Science & Technology Vision.2017.5:13--19.
[10]
Hai Peng Wang. Research on Unsteady Aerodynamic Characteristics and Optimal Design of Wind Turbine[D]. Dalian University of Technology. 2017.
[11]
Dai Binbin. Optimal Design and FluidsStructure Interaction
[12]
Characteristics of Wind Turbine Blades[D]. Xiangtan University. 2013.
[13]
WAN Quanxi, ZHANG Minghui, WU Jialong. Optimization Design and 3D Modeling for Wind Turbine Blades[J]. MACHINE TOOL & HYDRAULICS.2013,5:163--171.
Index Terms
- Multi-objective optimization design of small wind turbine blade
Recommendations
Optimization Real Time Parametric Simulation of Light Wind Turbine
CSIE '09: Proceedings of the 2009 WRI World Congress on Computer Science and Information Engineering - Volume 07This article for the purpose in here is to discuss optimization of the whole light wind turbine system design and analysis of the comparison results with physical wind turbine in Yangmingshan, Taipei (460m height Yangming Mountain) and simulate data. ...
Wind turbine bionic blade design and performance analysis
AbstractWith the growing shortage of energy, wind power is receiving an increasing amount of attention worldwide as a clean source of renewable energy. One of the most important components of the wind turbine is the bird-wing-like blade under ...
Comments
Please enable JavaScript to view thecomments powered by Disqus.Information & Contributors
Information
Published In
November 2019
528 pages
ISBN:9781450361910
DOI:10.1145/3378065
Copyright © 2019 ACM.
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]
In-Cooperation
- Guilin: Guilin University of Technology, Guilin, China
- Wuhan University of Technology: Wuhan University of Technology, Wuhan, China
- International Engineering and Technology Institute, Hong Kong: International Engineering and Technology Institute, Hong Kong
Publisher
Association for Computing Machinery
New York, NY, United States
Publication History
Published: 08 April 2020
Check for updates
Author Tags
Qualifiers
- Short-paper
- Research
- Refereed limited
Conference
ICIIP 2019
ICIIP 2019: 2019 4th International Conference on Intelligent Information Processing
November 16 - 17, 2019
China, China
Acceptance Rates
Overall Acceptance Rate 87 of 367 submissions, 24%
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- 0Total Citations
- 57Total Downloads
- Downloads (Last 12 months)2
- Downloads (Last 6 weeks)0
Reflects downloads up to 21 Nov 2024
Other Metrics
Citations
View Options
Login options
Check if you have access through your login credentials or your institution to get full access on this article.
Sign in