Estimation of the Tower Shape Effect on the Stress–Strain Behavior of Wind Turbines Operating under Offshore Boundary Conditions

The metal tower, or the pylon, is one of the most important elements in the construction of a wind turbine. It has the role of supporting the entire wind turbine, and it also allows access for inspection and conducting planned maintenance and repairs. Moreover, the tower ensures support for the structure and strengthens the whole assembly. It has a particularly important role, as it has to face very severe weather conditions. The present study aims to analyze the forces and moments resulting from the action of the wind on the tower of a wind turbine. Two important load cases are considered, namely, the load under operating conditions and the ultimate load under 50 year wind conditions. For this purpose, cylindrical and conical geometric shapes of the tower were chosen. These were analyzed under the action of both normal and extreme wind speeds. Then, the behavior of the two towers under the action of the wind speed for a location in the Black Sea was analyzed. Finally, in an attempt to make the structure more economical, the thickness of the shell was reduced.

Extreme wind speed prediction in mountainous area with mixed wind climates

In addition to common synoptic wind system, the mountainous terrain forms a local thermally driven wind system, which makes the mountain wind system have strong terrain dependence. Therefore, in order to estimate the reliable design wind speeds for structural safety, the samples for extreme wind speeds for certain return periods at mountainous areas can only come from field measurements at construction site. However, wind speeds measuring duration is usually short in real practice. This work proposes a novel method for calculating extreme wind speeds in mountainous areas by using short-term field measurement data and long-term nearby meteorological observatory data. Extreme wind speeds in mountainous area are affected by mixed climates composed by local-scale wind and large scale synoptic wind. The local winds can be recorded at construction site with short observatory time, while the extreme wind speeds samples from synoptic wind climate from nearby meteorological station with long observatory time is extracted for data augmentation. The bridge construction site at Hengduan Mountains in southwestern China is taken as an example in this study. A 10-month dataset of field measurement wind speeds is recorded at this location. This study firstly provides a new method to extract wind speed time series of windstorms. Based on the different windstorm features, the local and synoptic winds are separated. Next, the synoptic wind speeds from nearby meteorological stations are converted and combined with local winds to derive the extreme wind speeds probability distribution function. The calculation results shows that the extreme wind speed in the short return period is controlled by the local wind system, and the long-period extreme wind speed is determined by the synoptic wind system in the mountain area.

An Improved Typhoon Simulation Method Based On Latin Hypercube Sampling Method

In order to further improve the prediction accuracy of typhoon simulation method for extreme wind speed in typhoon prone areas, an improved typhoon simulation method is proposed by introducing the Latin hypercube sampling method into the traditional typhoon simulation method. In this paper, the improved typhoon simulation method is first given a detailed introduction. Then, this method is applied to the prediction of extreme wind speeds under various return periods in Hong Kong. To validate this method, two aspects of analysis is carried out, including correlation analysis among typhoon key parameters and prediction of extreme wind speeds under various return periods. The results show that the correlation coefficients among typhoon key parameters can be maintained satisfactorily with this improved typhoon simulation method. Compared with the traditional typhoon simulation method, extreme wind speeds under various return periods obtained with this improved typhoon simulation method are much closer to the results obtained with historical typhoon wind data.

The Compound Inverse Rayleigh as an Extreme Wind Speed Distribution and its Bayes Estimation

The paper deals with the Compound Inverse Rayleigh distribution, shown to constitute a proper model for the characterization of the probability distribution of extreme values of wind-speed, a topic which is gaining growing interest in the field of renewable generation assessment, both in view of wind power production evaluation and the wind-tower mechanical reliability and safety. The first part of the paper illustrates such model starting from its origin as a generalization of the Inverse Rayleigh model - already proven to be a valid model for extreme wind-speeds - by means of a continuous mixture generated by a Gamma distribution on the scale parameter, which gives rise to its name. Moreover, its validity to interpret different field data is illustrated, also by means of numerous numerical examples based upon real wind speed measurements. Then, a novel Bayes approach for the estimation of such extreme wind-speed model is proposed. The method relies upon the assessment of prior information in a practical way, that should be easily available to system engineers. In practice, the method allows to express one’s prior beliefs both in terms of parameters, as customary, and/or in terms of probabilities. The results of a large set of numerical simulations – using typical values of wind-speed parameters - are reported to illustrate the efficiency and the accuracy of the proposed method. The validity of the approach is also verified in terms of its robustness with respect to significant differences compared to the assumed prior information.

A probabilistic model for estimating ocean-spray distribution in extreme tropical cyclone winds

ABSTRACT. Serious gaps in knowledge about ocean spray at wind speeds over 28 m/s remain difficult to fill by observation or experiment; yet refined study of the thermodynamics of Tropical Cyclones (including typhoons and hurricanes) requires assessment of the hypothesis that ‘spray cooling’ at extreme wind speeds may act to reduce (i) the initial temperature of saturated air rising in the eyewall and so also (ii) the input of mechanical energy into the airflow as a whole. Such progressive reductions at higher speeds could, for example, make any possible influence, of future global warming on Tropical Cyclone intensification largely se1f-limiting. In order to help in extrapolation of knowledge on ocean spray to extreme wind speeds, a probabilistic analysis is introduced which allows for the effects of gusts, gravity and evaporation on droplet distributions yet all other respect is as simple as possible. Preliminary indications from this simplified analysis appear to confirm the potential importance of spray cooling.

Non-stationary statistical estimation of wind speeds of rare recurrence in the Azov and Black Sea region

In the paper statistical distribution of the highest wind speed per year in the Azov and Black Sea region was analyzed using the data of 33 meteorological stations for 1958-2013. A statistical estimation of the wind speed extremes was carried out by approximation of the empirical sample with a function of Generalized distribution of Extreme Values (GEV) and by extrapolating it to the low probabilities region. We used two methodologies and applied statistical distribution functions corresponding to them. The first method is based on the assumption of stationarity of parameters of the GEV function. The second one is based on the non-stationary assumption of time dependence of extremum localization parameter μ. It was found, that for 13 out of 33 stations of the region, non-stationary GEV-function turned out to be adequate to describe extreme wind speeds.

Hindcasts of Sea Surface Wind around the Korean Peninsula Using the WRF Model: Added Value Evaluation and Estimation of Extreme Wind Speeds

Sea surface wind plays an essential role in the simulating and predicting ocean phenomena. However, it is difficult to obtain accurate data with uniform spatiotemporal scale. A high-resolution (10 km) sea surface wind hindcast around the Korean Peninsula (KP) is presented using the weather research and forecasting model focusing on wind speed. The hindcast data for 39 years (1979–2017) are obtained by performing a three-dimensional variational analysis data assimilation, using ERA-Interim as initial and boundary conditions. To evaluate the added value of the hindcasts, the ASCAT-L2 satellite-based gridded data (DASCAT) is employed and regarded as “True” during 2008–2017. Hindcast and DASCAT data are verified using buoy observations from 1997–2017. The added value of the hindcast compared to ERA-Interim is evaluated using a modified Brier skill score method and analyzed for seasonality and wind intensity. Hindcast data primarily adds value to the coastal areas of the KP, particularly over the Yellow Sea in the summer, the East Sea in the winter, and the Korean Strait in all seasons. In case of strong winds (10–25 m·s−1), the hindcast performed better in the East Sea area. The estimation of extreme wind speeds is performed based on the added value and 50-year and 100-year return periods are estimated using a Weibull distribution. The results of this study can provide a reference dataset for climate perspective storm surge and wave simulation studies.

Extreme windstorms and sting-jets in convection-permitting climate simulations over Europe

Extra-tropical windstorms are one of the costliest natural hazards affecting Europe, and windstorms that develop a sting-jet are extremely damaging. A sting-jet is a mesoscale core of very high wind speeds that occurs in Shapiro-Keyser type cyclones, and high-resolution models are required to adequately model sting-jets. Here, we develop a low-cost methodology to automatically detect sting jets, using the characteristic warm seclusion of Shapiro-Keyser cyclones and the slantwise descent of high wind speeds, within pan-European 2.2km convection-permitting climate model (CPM) simulations over Europe. The representation of wind gusts is improved with respect to ERA-Interim reanalysis data compared to observations; this is linked to better representation of cold conveyor belts and sting-jets in the CPM. Our analysis indicates that Shapiro-Keyser cyclones, and those that develop sting-jets, are the most damaging windstorms in present and future climates. The frequency of extreme windstorms is projected to increase by 2100 and a large contribution comes from sting-jet storms. Furthermore, extreme wind speeds and their future changes are underestimated in the GCM compared to the CPM. We conclude that the CPM adds value in the representation of extreme winds and surface wind gusts and can provide improved input for impact models compared to coarser resolution models.

Simulating synthetic tropical cyclone tracks for statistically reliable wind and pressure estimations

The design of coastal protection measures and the quantification of coastal risks at locations affected by tropical cyclones (TCs) are often based solely on the analysis of historical cyclone tracks. Due to data scarcity and the random nature of TCs, the assumption that a hypothetical TC could hit a neighboring area with equal likelihood to past events can potentially lead to over- and/or underestimations of extremes and associated risks. The simulation of numerous synthetic TC tracks based on (historical) data can overcome this limitation. In this paper, a new method for the generation of synthetic TC tracks is proposed. The method has been implemented in the highly flexible open-source Tropical Cyclone Wind Statistical Estimation Tool (TCWiSE). TCWiSE uses an empirical track model based on Markov chains and can simulate thousands of synthetic TC tracks and wind fields in any oceanic basin based on any (historical) data source. Moreover, the tool can be used to determine the wind extremes, and the output can be used for the reliable assessment of coastal hazards. Validation results for the Gulf of Mexico show that TC patterns and extreme wind speeds are well reproduced by TCWiSE.