scholarly journals Investigation on Optimization Design of Offshore Wind Turbine Blades based on Particle Swarm Optimization

Energies ◽  
2019 ◽  
Vol 12 (10) ◽  
pp. 1972 ◽  
Author(s):  
Yong Ma ◽  
Aiming Zhang ◽  
Lele Yang ◽  
Chao Hu ◽  
Yue Bai
Keyword(s):  
Particle Swarm Optimization ◽  
Wind Turbine ◽  
Optimization Design ◽  
Oscillation Amplitude ◽  
Particle Swarm ◽  
Offshore Wind ◽  
Offshore Wind Turbine ◽  
Swarm Optimization ◽  
Wind Speeds ◽  
Floating Wind Turbine

Offshore wind power has become an important trend in global renewable energy development. Based on a particle swarm optimization (PSO) algorithm and FAST program, a time-domain coupled calculation model for a floating wind turbine is established, and a combined optimization design method for the wind turbine’s blade is developed in this paper. The influence of waves on the power of the floating wind turbine is studied in this paper. The results show that, with the increase of wave height, the power fluctuation of the wind turbine increases and the average power of the wind turbine decreases. With the increase of wave period, the power oscillation amplitude of the wind turbine increases, and the power of the wind turbine at equilibrium position decreases. The optimal design of the offshore floating wind turbine blade under different wind speeds is carried out. The results show that the optimum effect of the blades is more obvious at low and mid-low wind speeds than at rated wind speeds. Considering the actual wind direction distribution in the sea area, the maximum power of the wind turbine can be increased by 3.8% after weighted optimization, and the chord length and the twist angle of the blade are reduced.

Fault Diagnosis of Wind Turbine Gearbox Based on Improved QPSO Algorithm

2019 ◽  
Vol 12 (3) ◽  
pp. 277-283
Author(s):  
Jiatang Cheng ◽  
Yan Xiong
Keyword(s):  
Particle Swarm Optimization ◽  
Fault Diagnosis ◽  
Wind Turbine ◽  
Bp Neural Network ◽  
Quantum Particle ◽  
Particle Swarm ◽  
Wind Turbine Gearbox ◽  
Bp Network ◽  
Swarm Optimization ◽  
Quantum Particle Swarm Optimization

Background: The effective diagnosis of wind turbine gearbox fault is an important means to ensure the normal and stable operation and avoid unexpected accidents. Methods: To accurately identify the fault modes of the wind turbine gearbox, an intelligent diagnosis technology based on BP neural network trained by the Improved Quantum Particle Swarm Optimization Algorithm (IQPSOBP) is proposed. In IQPSO approach, the random adjustment scheme of contractionexpansion coefficient and the restarting strategy are employed, and the performance evaluation is executed on a set of benchmark test functions. Subsequently, the fault diagnosis model of the wind turbine gearbox is built by using IQPSO algorithm and BP neural network. Results: According to the evaluation results, IQPSO is superior to PSO and QPSO algorithms. Also, compared with BP network, BP network trained by Particle Swarm Optimization (PSOBP) and BP network trained by Quantum Particle Swarm Optimization (QPSOBP), IQPSOBP has the highest diagnostic accuracy. Conclusion: The presented method provides a new reference for the fault diagnosis of wind turbine gearbox.

The Current Situation and Recent Advances of Deep-Water Floating Wind Turbine

2012 ◽  
Vol 226-228 ◽  
pp. 772-775
Author(s):  
Yu Chen ◽  
Chun Li ◽  
Wei Gao ◽  
Jia Bin Nie
Keyword(s):  
Wind Turbine ◽  
Deep Water ◽  
Rapid Development ◽  
Coupled Model ◽  
Wind Farms ◽  
International Standards ◽  
Offshore Wind ◽  
Current Status ◽  
Offshore Wind Turbine ◽  
Floating Wind Turbine

Offshore wind turbine is a novel approach in the field of wind energy technology. With the rapid development of coastal wind farms, it is the trend to move them outward to deep-water district. However, the cost of construction rises significantly with the increase in water depth. Floating wind turbine is one of the efficient methods to solve this problem. The early history, current status and cutting-edge improvements of overseas offshore floating wind turbine as well as the shortcomings shall be presented. The concept designs, international standards, fully coupled model simulations and hydrodynamic experiments will be illustrated and discussed together with the development of the theory and the related software modules. Thus a novel researching method and concept shall be presented to provide reference for future researches

scholarly journals Mooring Line Damping Estimation for a Floating Wind Turbine

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Dongsheng Qiao ◽  
Jinping Ou
Keyword(s):  
Wind Turbine ◽  
Estimation Method ◽  
Excitation Amplitude ◽  
Dynamic Responses ◽  
Offshore Wind ◽  
Scale Model ◽  
Mooring Line ◽  
Offshore Wind Turbine ◽  
Floating Wind Turbine ◽  
Excitation Period

The dynamic responses of mooring line serve important functions in the station keeping of a floating wind turbine (FWT). Mooring line damping significantly influences the global motions of a FWT. This study investigates the estimation of mooring line damping on the basis of the National Renewable Energy Laboratory 5 MW offshore wind turbine model that is mounted on the ITI Energy barge. A numerical estimation method is derived from the energy absorption of a mooring line resulting from FWT motion. The method is validated by performing a 1/80 scale model test. Different parameter changes are analyzed for mooring line damping induced by horizontal and vertical motions. These parameters include excitation amplitude, excitation period, and drag coefficient. Results suggest that mooring line damping must be carefully considered in the FWT design.

Shape Optimization Design of Gravity Buttress of Arch Dam Based on Asynchronous Particle Swarm Optimization Method

2014 ◽  
Vol 662 ◽  
pp. 160-163
Author(s):  
Lei Xu
Keyword(s):  
Particle Swarm Optimization ◽  
Optimization Design ◽  
Design Method ◽  
Particle Swarm ◽  
Optimization Method ◽  
Arch Dam ◽  
Swarm Optimization ◽  
Safety Coefficient ◽  
Parametric Description ◽  
Particle Swarm Optimization Method

The optimization design method was rarely used to design the gravity buttress of arch dam in the past. With this in mind, the parametric description of gravity buttress is given, and the auto-calculation of its exerting loads and the safety coefficient of anti-slide stability are realized subsequently. Then, the optimization design model of gravity buttress and the procedures of optimization design are presented using the asynchronous particle swarm optimization method. Finally, ODGB software, which is short for Optimization Design of Gravity Buttress software, is developed and verified.

Sign in / Sign up

Export Citation Format

Share Document