Relative Motion During Single Blade Installation: Measurements From the North Sea

2020 ◽  
Author(s):  
Aljoscha Sander ◽  
Andreas F. Haselsteiner ◽  
Kader Barat ◽  
Michael Janssen ◽  
Stephan Oelker ◽  
...  
Keyword(s):  
Wind Speed ◽  
Wave Height ◽  
North Sea ◽  
Relative Motion ◽  
Significant Wave Height ◽  
Offshore Wind ◽  
Wave Excitation ◽  
Significant Wave ◽  
The North ◽  
The North Sea

Abstract During single blade installation in offshore wind farms, relative motion between nacelle and blade root due to wind and wave excitation pose a significant challenge. Wave excitation can be modelled considerably well by employing state-of-the-art simulation tools and can, therefore, be included in installation planning. Other phenomena, such as flow-induced vibrations are hard to capture and hence challenging to account for when defining installation procedures and limitations. Here, we present measurements conducted during the installation of an offshore wind farm consisting of multi-megawatt turbines installed on monopile foundations in the North Sea. A custom-built sensor capturing linear & angular acceleration and GPS-data was deployed atop the nacelle. Both partially and fully assembled turbines displayed complex oscillation orbits, swiftly changing amplitude and direction. Mean nacelle deflection correlated strongly with significant wave height as well as mean wind speed. As wind speed and significant wave height showed a strong correlation as well, it is difficult to discern which load drives the observed relative motions. While wind loads are significantly smaller than wave loads on partially assembled turbines under installation conditions, additional momentum induced by vortex shedding may prove sufficient to cause the observed effects.

scholarly journals Wave Climate Change in the North Sea and Baltic Sea

2019 ◽  
Vol 7 (6) ◽  
pp. 166 ◽  
Author(s):  
Antonio Bonaduce ◽  
Joanna Staneva ◽  
Arno Behrens ◽  
Jean-Raymond Bidlot ◽  
Renate Anna Irma Wilcke
Keyword(s):  
Climate Change ◽  
Baltic Sea ◽  
Wave Height ◽  
North Sea ◽  
Significant Wave Height ◽  
Wave Climate ◽  
Significant Wave ◽  
The North ◽  
The North Sea

Wave climate change by the end of the 21st century (2075–2100) was investigated using a regional wave climate projection under the RCP 8.5 scenario. The performance of the historical run (1980–2005) in representing the present wave climate was assessed when compared with in situ (e.g., GTS) and remote sensing (i.e., Jason-1) observations and wave hindcasts (e.g., ERA5-hindcast). Compared with significant wave height observations in different subdomains, errors on the order of 20–30% were observed. A Principal Component (PC) analysis showed that the temporal leading modes obtained from in situ data were well correlated (0.9) with those from the historical run. Despite systematic differences (10%), the general features of the present wave climate were captured by the historical run. In the future climate projection, with respect to the historical run, similar wave climate change patterns were observed when considering both the mean and severe wave conditions, which were generally larger during summer. The range of variation in the projected extremes (±10%) was consistent with those observed in previous studies both at the global and regional spatial scales. The most interesting feature was the projected increase in extreme wind speed, surface Stokes drift speed and significant wave height in the Northeast Atlantic. On the other hand, a decrease was observed in the North Sea and the southern part of the Baltic Sea basin, while increased extreme values occurred in the Gulf of Bothnia during winter.

scholarly journals MISALIGNMENT AND LAG TIME OF WIND AND WAVE OCCURRENCE BASED ON 10 YEARS MEASUREMENTS IN THE NORTH SEA NEAR THE GERMAN COAST

2018 ◽  
pp. 13
Author(s):  
Arndt Hildebrandt ◽  
Remo Cossu
Keyword(s):  
Wind Speed ◽  
Wave Height ◽  
North Sea ◽  
Offshore Wind ◽  
Wave Loads ◽  
Wind Speeds ◽  
The North ◽  
The North Sea ◽  
The Impact ◽  
The Waves

There are several intentions to analyze the correlation of wind and wave data, especially in the North Sea. Fatigue damage is intensified by wind and wave loads acting from different directions, due to the misaligned aerodynamic damping of the rotor regarding the wave loads from lateral directions. Furthermore, construction time and costs are mainly driven by the operational times of the working vessels, which strongly depend on the wind and wave occurrence and correlation. Turbulent wind can rapidly change its direction and intensity, while the inert water waves react slowly in relation to the wind profile. Tuerk (2008) investigates the impact of wind and turbulence on offshore wind turbines by analyzing data of four years. The study shows that the wave height is increasing with higher wind speeds but when the wind speed drops the reaction of the waves is postponed. The dependence of the wave height on the wind speed is varying because of the atmospheric stability and different wind directions. Fischer et al. (2011) estimated absolute values of misalignment between wind and waves located in the Dutch North Sea. The study presents decreasing misalignment for increasing wind speeds, ranging up to 90 degrees for wind speeds below 12 m/s and up to 30 degrees for wind speeds above 20 m/s. Bredmose et al. (2013) present a method of offshore wind and wave simulation by using metocean data. The study describes characteristics of the wind and wave climate for the North and Baltic Sea as well as the directional distribution of wind and waves. Güner et al. (2013) cover the development of a statistical wave model for the Karaburun coastal zone located at the southwest coast of the Black Sea with the help of wind and wave measurements and showed that the height of the waves is directly correlating with the duration of the wind for the last four hours.

Comparison of Bivariate Models of the Distribution of Significant Wave Height and Peak Wave Period

2007 ◽  
Author(s):  
Catarina S. Soares ◽  
C. Guedes Soares
Keyword(s):  
Wave Height ◽  
Significant Wave Height ◽  
Bivariate Normal Distribution ◽  
Wave Period ◽  
Peak Period ◽  
Data Set ◽  
Significant Wave ◽  
The North ◽  
Bivariate Models ◽  
The North Sea

This paper presents the results of a comparison of the fit of three bivariate models to a set of 14 years of significant wave height and peak wave period data from the North Sea. One of the methods defines the joint distribution from a marginal distribution of significant wave height and a set of distributions of peak period conditional on significant wave height. Other method applies the Plackett model to the data and the third one applies the Box-Cox transformation to the data in order to make it approximately normal and then fits a bivariate normal distribution to the transformed data set. It is shown that all methods provide a good fit but each one have its own strengths and weaknesses, being the choice dependent on the data available and applications in mind.

Validation of ERS-2 SAR offshore wind-speed maps in the North Sea

2004 ◽  
Vol 25 (19) ◽  
pp. 3817-3841 ◽  
Author(s):  
C. B. Hasager ◽  
E. Dellwik ◽  
M. Nielsen ◽  
B. R. Furevik
Keyword(s):  
Wind Speed ◽  
North Sea ◽  
Offshore Wind ◽  
The North ◽  
The North Sea

Validation of SARAL/AltiKa significant wave height and wind speed observations over the North Indian Ocean

2015 ◽  
Vol 135 ◽  
pp. 174-180 ◽  
Author(s):  
U. Mahesh Kumar ◽  
D. Swain ◽  
S.K. Sasamal ◽  
N. Narendra Reddy ◽  
T. Ramanjappa
Keyword(s):  
Wind Speed ◽  
Indian Ocean ◽  
Wave Height ◽  
Significant Wave Height ◽  
North Indian Ocean ◽  
Significant Wave ◽  
The North

scholarly journals SARAL-AltiKa Wind and Significant Wave Height for Offshore Wind Energy Applications in the New England Region

2020 ◽  
Vol 13 (1) ◽  
pp. 57
Author(s):  
Xinba Li ◽  
Panagiotis Mitsopoulos ◽  
Yue Yin ◽  
Malaquias Peña
Keyword(s):  
Wind Speed ◽  
Wind Energy ◽  
New England ◽  
Wave Height ◽  
Significant Wave Height ◽  
Surface Wind ◽  
Offshore Wind ◽  
Significant Wave ◽  
In Situ Observations

The SARAL-AltiKa dataset was evaluated for refined offshore wind energy resources assessment and potential metocean monitoring capability in the Southern New England region. Surface wind speed and Significant Wave Height (Hs) products were assessed with corresponding variables from buoy observations for 2014–2019. To increase the sample size, this study analyzed and applied an approach to collect data around the reference buoys beyond the satellite footprint at the expense of a bias increment. The study corroborated the accuracy of the SARAL-AltiKa measurements for the offshore area of interest and added details for stations closer to the coast compared with past studies. A proportional bias with underestimation of high values of Hs was found in coastal sites. Wind speed estimates on the other hand appear to be less sensitive to the closeness to the coast. The empirical relationship between wind strength and Hs in the buoy observations is reproduced to a large extent by the AltiKa measurements in locations where land contamination is minimal. The histograms of surface wind and Hs are well described by the Weibull distribution and the shape and scale parameters closely resemble those of the histograms of the collocated in situ observations. We use these results to extrapolate the winds to a target domain with no in situ observations for wind energy resource estimation.

Analysis of Offshore Wind Turbine Operation and Maintenance Using a Novel Time Domain Meteo-Ocean Modeling Approach

2012 ◽  
Author(s):  
I. Dinwoodie ◽  
F. Quail ◽  
D. McMillan
Keyword(s):  
Wind Speed ◽  
Wind Turbine ◽  
Wave Height ◽  
Time Domain ◽  
Significant Wave Height ◽  
Offshore Wind ◽  
Offshore Wind Turbine ◽  
Significant Wave ◽  
Modeling Approach ◽  
Operation And Maintenance

This paper presents a novel approach to repair modeling using a time domain Auto-Regressive model to represent meteo-ocean site conditions. The short term hourly correlations, medium term access windows of periods up to days and the annual distribution of site data are captured. In addition, seasonality is included. Correlation observed between wind and wave site can be incorporated if simultaneous data exists. Using this approach a time series for both significant wave height and mean wind speed is described. This allows MTTR to be implemented within the reliability simulation as a variable process, dependent on significant wave height. This approach automatically captures site characteristics including seasonality and allows for complex analysis using time dependent constraints such as working patterns to be implemented. A simple cost model for lost revenue determined by the concurrent simulated wind speed is also presented. A preliminary investigation of the influence of component reliability and access thresholds at various existing sites on availability is presented demonstrating the ability of the modeling approach to offer new insights into offshore wind turbine operation and maintenance.

scholarly journals PREDICTION OF THE SEVEREST SIGNIFICANT WAVE HEIGHT

1980 ◽  
Vol 1 (17) ◽  
pp. 35 ◽  
Author(s):  
Michel K. Ochi ◽  
Joseph E. Whalin
Keyword(s):  
Wave Height ◽  
Significant Wave Height ◽  
Current Method ◽  
Cumulative Distribution ◽  
Significant Wave ◽  
The North ◽  
Nonlinear Minimization ◽  
Minimization Procedure ◽  
The North Sea ◽  
Precise Representation

This paper presents a method to statistically estimate the severest sea state (significant wave height) from the observed data. For the estimation of extreme significant wave height, a precise representation of the data by a certain probability function is highly desirable. Since we do not have any specific technique to meet this requirement, this situation seriously affects the reliability of the current method of predicting the severest sea condition. The author's method is to express asymptotically the cumulative distribution of the significant wave height as a combination of an exponential and power of the significant wave height. The parameters involved are determined numerically by a nonlinear minimization procedure. The method is applied to available significant wave height data measured in the North Sea, the Canadian coast, and the U.S. coast. The results of the analysis show that the data are well represented by the proposed method over the entire range of the cumulative distribution.

The Extremal Dependence of Storm Severity, Wind Speed and Surface Level Pressure in the Northern North Sea

2013 ◽  
Author(s):  
Ross Towe ◽  
Emma Eastoe ◽  
Jonathan Tawn ◽  
Yanyun Wu ◽  
Philip Jonathan
Keyword(s):  
Wind Speed ◽  
Wave Height ◽  
North Sea ◽  
Significant Wave Height ◽  
Significant Wave ◽  
Extremal Dependence ◽  
Spatial Domains ◽  
Reliable Design ◽  
Northern North Sea ◽  
Dependence Measures

Characterising the joint distribution of extremes of significant wave height and wind speed is critical for reliable design and assessment of marine structures. The extremal dependence of pairs of oceanographic variables can be characterised using one of a number of summary statistics, which describe the two different types of extremal dependence. Quantifying the type of extremal dependence is an essential pre-requisite to joint or spatial extreme value modelling, and ensures that appropriate model forms are employed. We estimate extremal dependence between storm peak significant wave height and storm peak wind speed (Hs, WS) for locations in a region of the northern North Sea. However, since the extremal dependence itself may vary with storm direction, we introduce new covariate-dependent forms of the extremal dependence measures that account for the direction of the storm. We discuss the implications of all of the estimates for marine design, including specification of joint design criteria for extended spatial domains, and statistical downscaling to incorporate the effects of climate change on design specification.

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