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Wednesday, 12 March 2014
16:30 - 18:00 Floating wind turbines
Science & Research  


Room: Llevant
Session description

The session covers design problems related to floating wind turbines and how current research is overcoming these hurdles through innovative platform concepts, experimental methods and mooring system analysis. In particular, technical and economic studies and analyses for three different novel concepts will be presented, including one vertical axis concept, a concrete platform design and a combined wind & wave energy device. In addition, a new methodology for experimental model testing with a focus on aerodynamics and control will be presented, as well as a detailed assessment on long-term mooring system loads.

Learning objectives

  • Learn about a novel experimental methodology for floating wind turbine aerodynamic and controller testing
  • Identify challenges and benefits of an innovative vertical axis concept
  • Understand the design and potential benefits and challenges of a concrete platform
  • Assess structural fatigue damage of a multi-modal wind/wave energy device
  • Learn about a new methodology capable of reproducing life cycle mooring loads
Lead Session Chair:
Denis Matha, University of Stuttgart, Germany

Co-chair(s):
Antoine Peiffer, Marine Innovation and Technology, United States
RAUL GUANCHE IH Cantabria, Spain
Co-authors:
RAUL GUANCHE (1) F P LUCIA MENESES (1) JAVIER SARMIENTO (1) CESAR VIDAL (1) IÑIGO LOSADA (1)
(1) IH Cantabria, SANTANDER, Spain

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Presenter's biography

Biographies are supplied directly by presenters at EWEA 2014 and are published here unedited

Raúl Guanche studied Civil engineering in the University of Cantabria, he finished his PhD on 2007. He has a strong specialization on fluid and structure interaction, coastal and maritime structures design, numerical and physical modeling. Since 2009 he is the head of the marine renewable energy and offshore engineering group at IH Cantabria.

Abstract

Long term mooring loads assessment on a semisubmersible wind platform

Introduction

Offshore wind floating platforms have recived much attention in the recent years due to the trend of the offshore wind industry to move into deeper waters [1], [2]. One of the keys of the floating platform design is the mooring system. It depends primarily on the environmental loads it will be subject on the installation area. For this reason it is very important to know the technical feasibility of a design at various potential sites to optimize the design.
The present work shows a new methodology capable to reproduce life cycle mooring loads on a semisubmersible wind platform.


Approach

Wind, waves and currents action determine the suitability of an specific design for an especific site. The availability of global databases of waves and wind open a new horizon of opportunities for the problem addressed.
On the present work long term loads due to wave and wind action will be adressed, thanks to wave and wind data bases. Long term current databases should be available to apply the present methodology in order to obtain a full set of loads due to the three main sources of loads on the mooring system. GOW 1.0 database (Global Ocean Waves), from IH Cantabria [3] has been used as well as the NCEP/NCAR reanalysis [4], which constitutes the longest and most up-to-date global reanalysis. This work propose an innovative methodology, integraing the environmental database and the statistic tools in the design of a mooring system for an offshore floating platform, that allows obtaining long term mooring loads at fairlead position and anchor position. The methodology to obtain the life cycle mooring loads has been applied over a semisubmersible platform design planned to be installed between 50-100 meters of water depth [1].
The methodology has been shown on figure 1, next the most significative steps are summarized:
• Selection of the most relevant statistical parameters characterizing conveniently each sea state.
• Selection a limited number of sea conditions to simulate in a numerical model that allowing to calculate the mooring loads at fairled position and anchor position. (Max-Diss algorithm)
• Calibration and validation de numerical tool with physical model test.
• Reconstruction the mooring loads lifecycle at fairlead position and anchor position using a radial basis function (RBF) [5].
The methodology designed in this work is shown in Figure 1.


Figure 1. Innovative methodology to obtain the life cycle mooring loads on a floating wind platform.


Main body of abstract

Long term data bases usually give a very detailed information, however this information cannot be used directly in order to reproduce long term loads data bases over the mooring system. Mainly because the most used numerical models used to reproduce floating platform behavior are very time consuming. Because of that reason a selection technic combined with an interpolation technic is here proposed in order to reduce the computing effort.

SELECTION OF SEA STATES REPRESENTATIVES
The aim of the selection process is to extract a subset of wave situations representative of available ocean conditions from reanalysis database. The MDA algorithm allows an automatic selection of a subset of sea states representative of wave climate at deep water in a methodology to transfer it to coastal areas by applying an interpolation technique (Camus et al., 2010). The multivariate data at deep water is defined as: X*i={Hs,i, Tm,i, θm,i, Wi, βm,i }; i=1,…,N, where N is the number of sea states, corresponding to years from 1958 to 2001. This reanalysis data is defined by scalar and directional parameters of different magnitudes which require a normalization and an implementation of the distance in the circle for the directional parameter in the MDA algorithm.
First, before starting with the selection technique a set of representative sea state parameters have to be defined. Those have to represent the most important dynamics involved on the analysis. The selected parameters are the followings:

a. Significant wave heigh (Hs)
b. Mean peak period (Tp).
c. Wave propagation direction (θm)
d. Houraly mean wind velocity (W).
e. Wind direction (βm)
Figure 2 summarizes the mathematical procedure of the MDA method,


Figure 2. Mathematical description of the methodology applied

NUMERICAL AND PHYSICAL MODELLING
In the present study it has used the numerical tool SESAM. In order to have a reliable tool, a set of physical tests have been carried out and used to calibrate and validate SESAM numerical model. The set of physical model test done includes decay tests, regular tests and irregular tests (See Figure 4). Figure 3 shows some captures from numerical modelling at SESAM.
According to the general methodology, once the numerical model was calibrated and validated, the 1000 selected sea conditions are simulated.


Figure 3. Numerical model analysis. SESAM from DNV.


Figure 4. Calibration and validation the numerical model. Physical model test.

RECONSTRUCTION THE MOORING LOADS LIFECYCLE
Finally, based on Camus et al., 2011 [5], an interpolation technique is used to reconstruct the time series of mooring loads parameters. In this work it has been used an interpolation technique based on radial basis functions (RBF).
This interpolation method consists in approximating the real-valued function f=f(x) by a weighted sum of radially symmetric basic function located in the scattered data points {x1, …, xM} where the associated real function values {f1, …, fM} are available.
Because a set of real data is not currently avalable, the next methodology has been used to check the methodology. It is well knowed that mooring loads are driven by incident energy [6], therefore to validate this technique it has been applied to predict the incident energy (wind and waves incident energy) long term series based on a limited number of cases (sea states).
Figure 5 shows the scatter plots of incident energy (E) versus the reconstructed energy (E*). To assess the quality of reconstruction based on the number of sea conditions selected, it has analyzed the BIAS index, the mean square error (RMSE), the scatter index (SI), and the correlation coefficient (ρ), for the Energy reconstruction considering a different number of cases selected.This statistics are shown in Figure 6.
The quality of the results, in terms of the statistics index analyzed, are excelent considering more than 500 sea conditions selected.


Figure 5. Scatter plot. Reconstructed incident energy (E*) versus real incident energy (E)


Figure 6. The BIAS index, the mean square error (RMSE), the scatter index (SI), and the correlation coefficient (ρ), for the Energy reconstruction.



Conclusion

This work has developed a innovative methodology for transfering the full data base of metocean conditions to a data base of force parameters, which is an improvement on the design methodology enabling a floating platform design suitability analysis. Other innovation of this work is the integration of different areas of knowledge, that has allowed the development of a powerfull tool, which will take a leap of quality in design of a offshore wind floating platform.
The good performance of the methodology is due to the good behavior of MDA selection and RBF interpolation. The MDA automatically selects M multivariate sea conditions uniformly distributed over data, covering the edges and sampling in first moment the variability of site conditions, secondly the variability of each families sea conditions, and finaly the variablity of globan ocean climate. This process is very convenient and necessary in the RBF interpolation.
Finally, the validation of results confirms that the proposed methodology is able to reproduce the full time series of mooring loads. The good performance of the methodology is due to the good behavior of MDA selection and RBF interpolation.
Next, the long term mooring system database will be reconstructed based on the calibrated SESAM numerical model once the methodology has been proven based on simplified model.


Acknowledgment
This work has been part of a research project SAEMar, which was financially supported by the Spanish Ministry of Science and Innovation (MICINN) and European Regional Development Fund (ERDF) within the National Scientific Research, Development and Technological Innovation Plan (National R+D+i Plan) .



Learning objectives
This work has developed a innovative methodology for transfering the full data base of metocean conditions to a data base of force parameters, which is an improvement on the design methodology enabling a floating platform design suitability analysis.

Therefore, this method enables a fast and simple way, pre-design of the mooring system of a floating structure anywhere, and thus to study the suitability of the platform design in different locations.


References
[1] Roddier, D., Cermelli, C., Aubault, A., Weinstein, A. (2010). WindFloat: A floating foundation for offshore wind turbines Journal of Renewable and Sustainable Energy 2 (3) , art. no. 033104
[2] Madjid Karimirad and Torgeir Moan (2012). “Feasibility of the application of a Spar-type Wind Turbine at a Moderate Water Depth.” Energie Procedia Volume 24, 2012, Pages 340–350.
[3] Reguero B.G., Menéndez, M., Méndez, F.J., Mínguez, R., Losada, I.J. (2012). A Global Ocean Wave (GOW) calibrated reanalysis from 1948 onwards. Coastal Engineering, Doi: 10.1016/j.coastaleng.2012.03.003
[4] Kalnay, E, M., R. Kanamitsu, W. Kistler, D. Collins, L. Deaven, M. Gandin, S. Iredell, G. Saha, J. White, Y. Woollen, M. Zhu, W. Chelliah, W. Ebisuzaki, J. Higgins, K.C. Janowiak, C. Mo, J. Ropelewski, A. Wang, R. Leetmaa, R. Reynolds, R. Jenne y D. Joseph (1996). The NCEP/NCAR 40-year reanalysis project. Bull. Amer. Meteor. Soc., 77, 437-470.
[5] Paula Camus, Fernando J. Mendez, Raul MedinaCamus P. (2009). “Metodologías para la definición del clima marítimo en aguas profundas y someras: Aplicaciones en el corto, medio y largo plazo”. Ph. D. Thesis. Universidad de Cantabria (España) octubre 2009.
[6] Guanche, Y., Guanche, R., Camus, P., Méndez, F.J. Medina, R. (2012) A multivariate approach to estimate design loads for offshore wind turbines. Wind Energy Journal. DOI: 10.1002/we.1542, WILEY.