Rotor optimization design of brushless doubly fed generator for offshore wind turbine

2017 ◽  
Author(s):  
Hao Wang ◽  
Fengge Zhang ◽  
Siyang Yu ◽  
Ming Lin ◽  
Dapeng Wang
Keyword(s):  
Wind Turbine ◽  
Optimization Design ◽  
Offshore Wind ◽  
Offshore Wind Turbine ◽  
Doubly Fed ◽  
Doubly Fed Generator

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.

Analysis of Mode and Dynamic Stability for Wind Turbine Rotating Blades

2018 ◽  
Vol 140 (5) ◽  
Author(s):  
Jian-Ping Zhang ◽  
Zhen Gong ◽  
Liang Guo ◽  
Helen Wu
Keyword(s):  
Wind Turbine ◽  
Dynamic Stability ◽  
Optimization Design ◽  
Turbine Blades ◽  
Great Influence ◽  
Offshore Wind ◽  
Von Mises Stress ◽  
Offshore Wind Turbine ◽  
Rotating Blades ◽  
Von Mises

For large-scale offshore wind turbine rotating blades (NREL 5MW), the theoretical model of vibration due to fluid-structure interaction (FSI) is established, and the basic equations for modal analysis are given. Based on ANSYS workbench platform, the blade modal characteristics at different rotating speeds are analyzed, and further research on dynamic stability is carried out. The results indicate that the FSI and the blade rotation have a great influence on modal frequencies, which increase with the rotating speed of the blade under FSI. When the frequency of the periodic wind speed is close to the first-order natural frequency of the blade, both the maximum flapping displacement and the maximum von Mises stress increase with time, and the vibration divergence appears. At the safe tower clearance of 4.50 m, the critical value of the blade maximum von Mises stress shows a linear upward trend with the increase of the elasticity modulus, which provides technical references for optimization design and safe operation of wind turbine blades.

Experimental Study for SPAR Type Floating Offshore Wind Turbine With Blade-Pitch Control

2013 ◽  
Author(s):  
Toshiki Chujo ◽  
Yoshimasa Minami ◽  
Tadashi Nimura ◽  
Shigesuke Ishida
Keyword(s):  
Wind Turbine ◽  
Wind Farm ◽  
Offshore Wind ◽  
Scale Model ◽  
Offshore Wind Turbine ◽  
Experimental Proof ◽  
Pitch Control ◽  
Model Experiments ◽  
North Eastern ◽  
North Eastern Part

The experimental proof of the floating wind turbine has been started off Goto Islands in Japan. Furthermore, the project of floating wind farm is afoot off Fukushima Prof. in north eastern part of Japan. It is essential for realization of the floating wind farm to comprehend its safety, electric generating property and motion in waves and wind. The scale model experiments are effective to catch the characteristic of floating wind turbines. Authors have mainly carried out scale model experiments with wind turbine models on SPAR buoy type floaters. The wind turbine models have blade-pitch control mechanism and authors focused attention on the effect of blade-pitch control on both the motion of floater and fluctuation of rotor speed. In this paper, the results of scale model experiments are discussed from the aspect of motion of floater and the effect of blade-pitch control.

scholarly journals Unsupervised Damage Detection for Offshore Jacket Wind Turbine Foundations Based on an Autoencoder Neural Network

Sensors ◽  
2021 ◽  
Vol 21 (10) ◽  
pp. 3333
Author(s):  
Maria del Cisne Feijóo ◽  
Yovana Zambrano ◽  
Yolanda Vidal ◽  
Christian Tutivén
Keyword(s):  
Neural Network ◽  
Wind Turbine ◽  
Environmental Conditions ◽  
Wind Farms ◽  
Offshore Wind ◽  
Offshore Wind Turbine ◽  
Small Subset ◽  
Scaled Model ◽  
Vibration Data ◽  
Large Water

Structural health monitoring for offshore wind turbine foundations is paramount to the further development of offshore fixed wind farms. At present time there are a limited number of foundation designs, the jacket type being the preferred one in large water depths. In this work, a jacket-type foundation damage diagnosis strategy is stated. Normally, most or all the available data are of regular operation, thus methods that focus on the data leading to failures end up using only a small subset of the available data. Furthermore, when there is no historical precedent of a type of fault, those methods cannot be used. In addition, offshore wind turbines work under a wide variety of environmental conditions and regions of operation involving unknown input excitation given by the wind and waves. Taking into account the aforementioned difficulties, the stated strategy in this work is based on an autoencoder neural network model and its contribution is two-fold: (i) the proposed strategy is based only on healthy data, and (ii) it works under different operating and environmental conditions based only on the output vibration data gathered by accelerometer sensors. The proposed strategy has been tested through experimental laboratory tests on a scaled model.

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