Heave damping of spar platform for offshore wind turbine with heave plate

2016 ◽  
Vol 121 ◽  
pp. 24-36 ◽  
Author(s):  
A. Subbulakshmi ◽  
R. Sundaravadivelu
Author(s):  
Tomoaki Utsunomiya ◽  
Iku Sato ◽  
Osamu Kobayashi ◽  
Takashi Shiraishi ◽  
Takashi Harada

A floating offshore wind turbine platform supporting a 2MW downwind-type turbine was successfully installed offshore of Kabashima Island, Goto city, Nagasaki prefecture, Japan on October 18, 2013. It has been operating since October 28, 2013 as the first grid-connected multi-megawatt floating wind turbine in Japan. The spar platform has a unique feature, that is, the upper part of the spar is made of steel (as usual) but the lower part is made of precast prestressed concrete (PC). Such a configuration is referred to as hybrid-spar. In this paper, the design methodology of the hybrid spar is presented — including environmental design conditions, DLCs (Design Load Cases), dynamic analysis, fatigue analysis, etc. Also, the installation procedure is presented briefly.


Author(s):  
Javier Moreno ◽  
Krish P. Thiagarajan ◽  
Matthew Cameron

Experiments were conducted on a 1:80 scaled column of the WindFloat semi-submersible floating offshore wind turbine platform. The structure was forced to oscillate at frequencies of up to 6 Hz and at various amplitudes to create a parameter space much larger than previously reported. The hydrodynamic coefficients of the column with a hexagonal heave plate were compared to the base case of a column with a circular heave plate. Results show remarkably similar behavior between the two cases over the range of parameters tested, but quite distinct from published data on square plates. At low Keulegan-Carpenter number, the hexagonal plate showed a slightly higher added mass, but the difference narrowed down with increasing KC. An opposite trend was noticed for the damping coefficients. Overall the maximum difference in damping was about 8%. The paper presents some of the challenges in experimenting over a large parameter range, and also analyzes the trends in data over the range. It is expected that the presented data will be of use with engineers attempting to use heave plates for stabilizing wind turbine platforms in range of wave and wind conditions to maximize wind energy generation efficiency.


Author(s):  
Toshiki Chujo ◽  
Yoshimasa Minami ◽  
Tadashi Nimura ◽  
Shigesuke Ishida

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.


Sensors ◽  
2021 ◽  
Vol 21 (10) ◽  
pp. 3333
Author(s):  
Maria del Cisne Feijóo ◽  
Yovana Zambrano ◽  
Yolanda Vidal ◽  
Christian Tutivén

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.


Sign in / Sign up

Export Citation Format

Share Document