JOINT PROBABILITY DISTRIBUTION MODEL OF WIND AND WAVES FOR OFFSHORE WIND TURBINE IN JAPAN SEA AREA

2019 ◽  
Vol 75 (2) ◽  
pp. I_31-I_36
Author(s):  
Yoji TANAKA ◽  
Takeshi YOSHIOKA ◽  
Keiji NAKAI ◽  
Toshihiko NAGAI
Keyword(s):  
Probability Distribution ◽  
Wind Turbine ◽  
Joint Probability ◽  
Japan Sea ◽  
Offshore Wind ◽  
Distribution Model ◽  
Offshore Wind Turbine ◽  
Joint Probability Distribution ◽  
Sea Area

Study on the Dynamic Response for Floating Foundation of Offshore Wind Turbine

2011 ◽  
Author(s):  
Yougang Tang ◽  
Jun Hu ◽  
Liqin Liu
Keyword(s):  
Wind Turbine ◽  
Wind Farm ◽  
Dynamic Responses ◽  
Offshore Wind ◽  
Offshore Wind Turbine ◽  
Wave Load ◽  
Mooring Lines ◽  
Floating Foundation ◽  
Wind Turbine System ◽  
Sea Area

The wind resources for ocean power generation are mostly distributed in sea areas with the distance of 5–50km from coastline, whose water depth are generally over 20m. To improve ocean power output and economic benefit of offshore wind farm, it is necessary to choose floating foundation for offshore wind turbine. According to the basic data of a 600kW wind turbine with a horizontal shaft, the tower, semi-submersible foundation and mooring system are designed in the 60-meter-deep sea area. Precise finite element models of the floating wind turbine system are established, including mooring lines, floating foundation, tower and wind turbine. Dynamic responses for the floating foundation of offshore wind turbine are investigated under wave load in frequency domain.

Comparison of Dynamic Response in a 2MW Floating Offshore Wind Turbine During Typhoon Approaches

2019 ◽  
Author(s):  
Koji Tanaka ◽  
Iku Sato ◽  
Tomoaki Utsunomiya ◽  
Hiromu Kakuya
Keyword(s):  
Dynamic Response ◽  
Wind Turbine ◽  
Atmospheric Pressure ◽  
Offshore Wind ◽  
Floating Body ◽  
Offshore Wind Turbine ◽  
Floating Offshore Wind Turbine ◽  
Maximum Wave Height ◽  
Sea Area ◽  
Good Agreement

Abstract In this paper, we describe the analysis of the dynamic response of a 2 MW floating offshore wind turbine (FOWT) at the time of typhoon attack in the actual sea area. In order to introduce floating offshore wind turbine in Asia, it is essential to evaluate the influence of typhoon attack accurately. This FOWT, named HAENKAZE is the only FOWT to operate commercially in areas where typhoons occur. On July 3rd, 2018, the strongest typhoon (Prapiroon) at the installed area of the FOWT since its installation approached the HAENKAZE. The central atmospheric pressure of the typhoon at the closest time was 965 hPa, the maximum instantaneous wind speed at the hub height was 52.2 m/s, and the maximum wave height was 7.1 m. In this paper, the dynamic response of the floating body at the time of typhoon attack is compared for the measured and the simulated values. As a result of the comparison, basically a good agreement has been obtained between the measured and the simulated values except for yaw response, for which the simulated values considerably overestimate the measured values.

Model Experiment of a SPAR Type Offshore Wind Turbine in Storm Condition

2012 ◽  
Author(s):  
Kentaroh Kokubun ◽  
Shigesuke Ishida ◽  
Tadashi Nimura ◽  
Toshiki Chujo ◽  
Shigeo Yoshida ◽  
...  
Keyword(s):  
Wind Turbine ◽  
Model Experiment ◽  
Wind Farms ◽  
Offshore Wind ◽  
Mooring Line ◽  
Offshore Wind Turbine ◽  
Ocean Engineering ◽  
Under Construction ◽  
Storm Condition ◽  
Sea Area

Wind power has the primary potential among renewable energies. Because Japan consists of little flat land and little shallow coast, floating wind turbine must be developed to make wind farms in Japan. Therefore, Japanese national demonstration project of Floating Offshore Wind Turbine (FOWT) was started in 2010FY by Ministry of the Environment and a SPAR-type FOWT is under construction at present. The floater is planned to be hybrid, consists of upper part by steal and lower part by pre-stressed concrete. Four fins are attached around the floater to suppress yaw motion. The floater is moored by three catenary chains. In order to confirm the safety of the FOWT in storm condition, experiments of a scale of 1/34.5 model were carried out at Ocean Engineering Basin of National Maritime Research Institute (NMRI), Japan. The draft of SPAR, the height of hub above sea level and the diameter of rotor of the model are 1.07m, 0.68m and 0.64m, respectively. In all experiments, blades are fixed to the hub under feathering condition and the hub is irrotational and fixed to the tower because this wind turbine is assumed to be under the storm condition, but wind blows transversely to the nacelle to give the maximum wind force. Water depth of the basin is smaller than the planned sea area on a reduced scale of model, therefore, springs and wires were used instead of chains in order to correspond to characteristics of horizontal mooring tension. Environmental forces are wind, wave and current in 50-year return period. Tensions of the 3 moorings and the motion of the model are measured in condition of wind and/or wave and/or current. Three kinds of direction of wind are adopted. One is the same direction as the wave and current, another is perpendicular to the wave and current, and the other is against to the wave and current. Besides the intact conditions a mooring-line-cut experiment in a storm condition was also conducted. Moreover, the effect of vortex induced motion (VIM), which occurs in current, was discussed. The results of the model experiment are reported to show the sufficient safety of this FOWT.

scholarly journals Copula-Based Method for Estimating the Minimum Void Ratio Parameters of Tailings Deposits

Geofluids ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Hao Li ◽  
Yichuan Tang ◽  
Shibo Li ◽  
Jianquan Ma ◽  
Xiaojie Zhao
Keyword(s):  
Probability Distribution ◽  
Fine Particle ◽  
Void Ratio ◽  
Joint Probability ◽  
Copula Function ◽  
Distribution Model ◽  
Joint Probability Distribution ◽  
Particle Content ◽  
Edge Distribution ◽  
Guarantee Rate

The pore ratio is an important parameter affecting the stability and safety of tailings reservoirs; however, the relationship between the pore ratio and physical properties of tailings sand has not been researched in-depth. In this paper, using the tailings from a tungsten mine in southern Shaanxi as a case study, the correlation between the minimum void ratio and related parameters is analyzed, based on laboratory test data, and the optimal marginal distribution function of the parameters is determined. The Gumbel-Hougard copula function that best describes the correlation between parameters is identified, and it is used to establish the joint probability distribution model of the three parameters, and the guarantee rate α is introduced to estimate and analyze the minimum void ratio. The results show that the optimal edge distribution of the fine particle content and specific gravity follows a truncated normal distribution, and the optimal edge distribution of the minimum void ratio follows a logarithmic normal distribution. According to AIC criterion, the Gumbel-Hougard copula is the best three-dimensional copula function to fit the minimum void ratio and related parameters. When the guarantee rate α is 0.485, the joint probability distribution model achieves optimal performance in terms of estimating the minimum void ratio. The maximum error of the estimation is 1.99%, which is verified through data, and the estimation meets the requirements for practical engineering. The method proposed in this paper uses the existing measured data to establish a joint probability distribution model and combines the collected fine particle content and specific gravity data with the guarantee rate to estimate the minimum void ratio, providing a novel basis for the study of the physical properties of tailings.

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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