Design and optimization of airfoils and a 20 kW wind turbine using multi-objective genetic algorithm and HARP_Opt code

被引:31
|
作者
Ram, Krishnil R. [1 ]
Lal, Sunil P. [2 ]
Ahmed, M. Rafiuddin [1 ]
机构
[1] Univ South Pacific, Div Mech Engn, Suva, Fiji
[2] Univ South Pacific, Sch Comp Informat & Math Sci, Suva, Fiji
关键词
Low Reynolds number airfoils; Genetic algorithm; Wind turbine; Blade design; VARIABLE-SPEED; TRANSITION;
D O I
10.1016/j.renene.2018.08.040
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Small wind turbines (SWTs) are ideal for supplying electricity to small remote communities that do not have grid access. However, literature review and trends point out that SWTs are far from fully developed. While larger wind turbines have been researched extensively and perfected, SWTs lack improvements in efficiency and capacity factor. In the present work, airfoil sections for a 20 kW wind turbine were generated using Multi-Objective Genetic Algorithm. The USP07-45XX family of airfoils was designed to achieve maximum lift-to-drag ratio from 4 to 10 degrees angles of attack and to be insensitive to leading edge roughness. The USP07-45XX airfoils showed only slight change during clean and soiled conditions both in experiments and in numerical studies. The optimized airfoils were used in the design of a 20 kW wind turbine. The turbine design and optimization code developed by National Renewable Energy Laboratory (NREL) - HARP_Opt - was used to design and optimize the 20 kW turbine. The turbine was designed using soiled airfoil characteristics of the USP07-45XX family of airfoils. Power curves show cut in speed of 2 m/s and a rated speed of 9 m/s. This gives an annual energy production (AEP) of 4.787 x 10(4) kWh while having leading edge soiling on blades. The high resistance of the airfoil to soiling means that the AEP will not vary from its design value due to the turbine blades getting dirty or soiled. (C) 2018 Elsevier Ltd. All rights reserved.
引用
收藏
页码:56 / 67
页数:12
相关论文
共 50 条
  • [1] Design and Optimisation of a 20kW Horizontal Axis Wind Turbine using HARP_Opt
    Singh, Krishneel A.
    Ahmed, Mohammed R.
    [J]. 2019 9TH INTERNATIONAL CONFERENCE ON POWER AND ENERGY SYSTEMS (ICPES), 2019,
  • [2] Optimization of Wind Turbine Blade Airfoils Using a Multi-Objective Genetic Algorithm
    Chen, Xiaomin
    Agarwal, Ramesh K.
    [J]. JOURNAL OF AIRCRAFT, 2013, 50 (02): : 519 - 527
  • [3] OPTIMIZATION OF FLATBACK AIRFOILS FOR WIND TURBINE BLADES USING A MULTI-OBJECTIVE GENETIC ALGORITHM
    Chen, Xiaomin
    Agarwal, Ramesh
    [J]. PROCEEDINGS OF THE ASME 6TH INTERNATIONAL CONFERENCE ON ENERGY SUSTAINABILITY - 2012, PTS A AND B, 2012, : 1313 - 1324
  • [4] Shape optimization of airfoils in transonic flow using a multi-objective genetic algorithm
    Chen, Xiaomin
    Agarwal, Ramesh K.
    [J]. PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART G-JOURNAL OF AEROSPACE ENGINEERING, 2014, 228 (09) : 1654 - 1667
  • [5] Multi-Objective Structural Optimization of Wind Turbine Tower Using Nondominated Sorting Genetic Algorithm
    Zheng, Yuqiao
    Zhang, Lu
    Dong, Fugang
    Dong, Bo
    [J]. Journal of Beijing Institute of Technology (English Edition), 2020, 29 (03): : 417 - 424
  • [6] Multi-Objective Structural Optimization of Wind Turbine Tower Using Nondominated Sorting Genetic Algorithm
    Yuqiao Zheng
    Lu Zhang
    Fugang Dong
    Bo Dong
    [J]. Journal of Beijing Institute of Technology, 2020, 29 (03) : 417 - 424
  • [7] Optimization of thick wind turbine airfoils using a genetic algorithm
    Jae-Ho Jeong
    Soo-Hyun Kim
    [J]. Journal of Mechanical Science and Technology, 2018, 32 : 3191 - 3199
  • [8] Optimization of thick wind turbine airfoils using a genetic algorithm
    Jeong, Jae-Ho
    Kim, Soo-Hyun
    [J]. JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY, 2018, 32 (07) : 3191 - 3199
  • [9] MULTI-OBJECTIVE OPTIMIZATION FOR FRANCIS TURBINE RUNNER USING GENETIC ALGORITHM
    Sato, Koma
    Tamura, Yuta
    Tani, Kiyohito
    [J]. PROCEEDINGS OF THE ASME INTERNATIONAL MECHANICAL ENGINEERING CONGRESS AND EXPOSITION, 2014, VOL 7, 2015,
  • [10] Multi-Objective Design Optimization of Multicopter using Genetic Algorithm
    Ayaz, Ahsan
    Rasheed, Ashhad
    [J]. PROCEEDINGS OF 2021 INTERNATIONAL BHURBAN CONFERENCE ON APPLIED SCIENCES AND TECHNOLOGIES (IBCAST), 2021, : 177 - 182