Design and Analysis of Offshore Wind Turbines: Problem Formulation and Optimization Techniques

被引:1
作者
Ghaemifard, Saeedeh [1 ]
Ghannadiasl, Amin [1 ]
机构
[1] Univ Mohaghegh Ardabili, Dept Civil Engn, Ardebil 5619911367, Iran
关键词
Optimization; Metaheuristic algorithm; Wind Turbine; Design; Wind Turbine Blade; PARTICLE SWARM OPTIMIZATION; GENETIC-ALGORITHM; STRUCTURAL OPTIMIZATION; NUMERICAL-SIMULATION; SHAPE OPTIMIZATION; GLOBAL PERFORMANCE; FARM; FATIGUE; FREQUENCY; PLACEMENT;
D O I
10.1007/s11804-024-00473-8
中图分类号
U6 [水路运输]; P75 [海洋工程];
学科分类号
0814 ; 081505 ; 0824 ; 082401 ;
摘要
Researchers often explore metaheuristic algorithms for their studies. These algorithms possess unique features for solving optimization problems and are usually developed on the basis of real-world natural phenomena or animal and insect behavior. Numerous fields have benefited from metaheuristic algorithms for solving real-world optimization problems. As a renewable energy source, offshore wind energy is a rapidly developing subject of research, attracting considerable interest worldwide. However, designing offshore wind turbine systems can be challenging because of the large space of design parameters and different environmental conditions, and the optimization of offshore wind turbines can be extremely expensive. Nevertheless, advanced optimization methods can help to overcome these challenges. This study explores the use of metaheuristic algorithms in optimizing the design of wind turbines, including wind farm layout and wind turbine blades. Given that offshore wind energy relies more heavily on subsidies than fossil fuel-based energy sources, lowering the costs for future projects, particularly by developing new technologies and optimizing existing methods, is crucial.
引用
收藏
页码:707 / 722
页数:16
相关论文
共 135 条
[1]   Optimization of wind turbines siting in a wind farm using genetic algorithm based local search [J].
Abdelsalam, Ali M. ;
El-Shorbagy, M. A. .
RENEWABLE ENERGY, 2018, 123 :748-755
[2]  
Ahmadpour F., 2021, J MECH ENG, V50, P171
[3]  
AlHamaydeh M.H., 2015, P 5 INT C COMPUTATIO, P3505, DOI DOI 10.7712/120115.3634.1443
[4]   Optimization of Support Structures for Offshore Wind Turbines Using Genetic Algorithm with Domain-Trimming [J].
AlHamaydeh, Mohammad ;
Barakat, Samer ;
Nasif, Omar .
MATHEMATICAL PROBLEMS IN ENGINEERING, 2017, 2017
[5]   Closed form solution of Eigen frequency of monopile supported offshore wind turbines in deeper waters incorporating stiffness of substructure and SSI [J].
Arany, Laszlo ;
Bhattacharya, S. ;
Macdonald, John H. G. ;
Hogan, S. John .
SOIL DYNAMICS AND EARTHQUAKE ENGINEERING, 2016, 83 :18-32
[6]   A 3D Study of the Darrieus Wind Turbine with Auxiliary Blades and Economic Analysis Based on an Optimal Design from a Parametric Investigation [J].
Asadbeigi, Mohammadreza ;
Ghafoorian, Farzad ;
Mehrpooya, Mehdi ;
Chegini, Sahel ;
Jarrahian, Azad .
SUSTAINABILITY, 2023, 15 (05)
[7]  
Ashuri T., 2012, Beyond classical upscaling: integrated aeroservoelastic design and optimization of large offshore wind turbines
[8]   Coupled dynamic analysis of multiple wind turbines on a large single floater [J].
Bae, Y. H. ;
Kim, M. H. .
OCEAN ENGINEERING, 2014, 92 :175-187
[9]   Structural Optimization Design of 2MW Composite wind turbine blade [J].
Bagherpoor, Toohid ;
Li Xuemin .
8TH INTERNATIONAL CONFERENCE ON APPLIED ENERGY (ICAE2016), 2017, 105 :1226-1233
[10]   Multiphysics simulations of the dynamic and wakes of a floating Vertical Axis Wind Turbine [J].
Balty, P. ;
Caprace, D. G. ;
Waucquez, J. ;
Coquelet, M. ;
Chatelain, P. .
SCIENCE OF MAKING TORQUE FROM WIND (TORQUE 2020), PTS 1-5, 2020, 1618