scholarly journals WEC-Sim Phase 1 Validation Testing: Experimental Setup and Initial Results

Author(s):  
Bret Bosma ◽  
Asher Simmons ◽  
Pedro Lomonaco ◽  
Kelley Ruehl ◽  
Budi Gunawan

In the wave energy industry, there is a need for open source numerical codes and publicly available experimental data, both of which are being addressed through the development of WEC-Sim by Sandia National Laboratories and the National Renewable Energy Laboratory (NREL). WEC-Sim is an open source code used to model wave energy converters (WECs) when subject to incident waves. In order for the WEC-Sim code to be useful, code verification and physical model validation is necessary. This paper describes the wave tank testing for the 1:33 scale experiments of a Floating Oscillating Surge Wave Energy Converter (FOSWEC). The WEC-Sim experimental data set will help to advance the wave energy converter industry by providing a free, high-quality data set for researchers and developers. This paper describes the WEC-Sim open source wave energy converter simulation tool, experimental validation plan, and presents preliminary experimental results from the FOSWEC Phase 1 testing.

Author(s):  
Kelley Ruehl ◽  
Carlos Michelen ◽  
Bret Bosma ◽  
Yi-Hsiang Yu

The Wave Energy Converter Simulator (WEC-Sim) is an open-source code jointly developed by Sandia National Laboratories and the National Renewable Energy Laboratory. It is used to model wave energy converters subjected to operational and extreme waves. In order for the WEC-Sim code to be beneficial to the wave energy community, code verification and physical model validation is necessary. This paper describes numerical modeling of the wave tank testing for the 1:33-scale experimental testing of the floating oscillating surge wave energy converter. The comparison between WEC-Sim and the Phase 1 experimental data set serves as code validation. This paper is a follow-up to the WEC-Sim paper on experimental testing, and describes the WEC-Sim numerical simulations for the floating oscillating surge wave energy converter.


2005 ◽  
Vol 128 (1) ◽  
pp. 56-64 ◽  
Author(s):  
Gaelle Duclos ◽  
Aurelien Babarit ◽  
Alain H. Clément

Considered as a source of renewable energy, wave is a resource featuring high variability at all time scales. Furthermore wave climate also changes significantly from place to place. Wave energy converters are very often tuned to suit the more frequent significant wave period at the project site. In this paper we show that optimizing the device necessitates accounting for all possible wave conditions weighted by their annual occurrence frequency, as generally given by the classical wave climate scatter diagrams. A generic and very simple wave energy converter is considered here. It is shown how the optimal parameters can be different considering whether all wave conditions are accounted for or not, whether the device is controlled or not, whether the productive motion is limited or not. We also show how they depend on the area where the device is to be deployed, by applying the same method to three sites with very different wave climate.


Author(s):  
Pedro C. Vicente ◽  
Anto´nio F. O. Falca˜o ◽  
Paulo A. P. Justino

Floating point absorbers devices are a large class of wave energy converters for deployment offshore, typically in water depths between 40 and 100m. As floating oil and gas platforms, the devices are subject to drift forces due to waves, currents and wind, and therefore have to be kept in place by a proper mooring system. Although similarities can be found between the energy converting systems and floating platforms, the mooring design requirements will have some important differences between them, one of them associated to the fact that, in the case of a wave energy converter, the mooring connections may significantly modify its energy absorption properties by interacting with its oscillations. It is therefore important to examine what might be the more suitable mooring design for wave energy devices, according to the converters specifications. When defining a mooring system for a device, several initial parameters have to be established, such as cable material and thickness, distance to the mooring point on the bottom, and which can influence the device performance in terms of motion, power output and survivability. Different parameters, for which acceptable intervals can be established, will represent different power absorptions, displacements from equilibrium position, load demands on the moorings and of course also different costs. The work presented here analyzes what might be, for wave energy converter floating point absorber, the optimal mooring configuration parameters, respecting certain pre-established acceptable intervals and using a time-domain model that takes into account the non-linearities introduced by the mooring system. Numerical results for the mooring forces demands and also motions and absorbed power, are presented for two different mooring configurations for a system consisting of a hemispherical buoy in regular waves and assuming a liner PTO.


Author(s):  
Eirini Katsidoniotaki ◽  
Edward Ransley ◽  
Scott Brown ◽  
Johannes Palm ◽  
Jens Engström ◽  
...  

Abstract Accurate modeling and prediction of extreme loads for survivability is of crucial importance if wave energy is to become commercially viable. The fundamental differences in scale and dynamics from traditional offshore structures, as well as the fact that wave energy has not converged around one or a few technologies, implies that it is still an open question how the extreme loads should be modeled. In recent years, several methods to model wave energy converters in extreme waves have been developed, but it is not yet clear how the different methods compare. The purpose of this work is the comparison of two widely used approaches when studying the response of a point-absorber wave energy converter in extreme waves, using the open-source CFD software OpenFOAM. The equivalent design-waves are generated both as equivalent regular waves and as focused waves defined using NewWave theory. Our results show that the different extreme wave modeling methods produce different dynamics and extreme forces acting on the system. It is concluded that for the investigation of point-absorber response in extreme wave conditions, the wave train dynamics and the motion history of the buoy are of high importance for the resulting buoy response and mooring forces.


2019 ◽  
Vol 183 ◽  
pp. 426-436 ◽  
Author(s):  
Simone Giorgi ◽  
Josh Davidson ◽  
Morten Jakobsen ◽  
Morten Kramer ◽  
John V. Ringwood

Author(s):  
Tunde O. Aderinto ◽  
Francisco Haces-Fernandez ◽  
Hua Li

Although theoretical available wave energy is higher than most of ocean energy sources, the commercial utilization of wave energy is much slower than other ocean energy sources. The difficulty of integration with the electrical grid system and the challenges of the installation, operation and maintenance of large energy generation and transmission systems are the major reasons. Even though there are successfully tested models of wave energy converters, the fact that wave energy is directly affected by wave height and wave period makes the actual wave energy output with high variation and difficult to be predicted. And most of the previous studies on wave energy and its utilization have focused on the large scale energy production that can be integrated into a power grid system. In this paper, the authors identify and discuss stand-alone wave energy converter systems and facilities that are not connected to the electricity grid with focus on small scale wave energy systems as potential source of energy. For the proper identification, qualification and quantification of wave energy resource potential, wave properties such as wave height and period need to be characterized. This is used to properly determine and predict the probability of the occurrence of these wave properties at particular locations, which enables the choice of product design, installation, operation and maintenance to effectively capture wave energy. Meanwhile, the present technologies available for wave energy converters can be limited by location (offshore, nearshore or shoreline). Therefore, the potential applications of small scale stand-alone wave energy converter are influenced by the demand, location of the need and the appropriate technology to meet the identified needs. The paper discusses the identification of wave energy resource potentials, the location and appropriate technology suitable for small scale wave energy converter. Two simplified wave energy converter designs are created and simulated under real wave condition in order to estimate the energy production of each design.


Author(s):  
Jennifer van Rij ◽  
Yi-Hsiang Yu ◽  
Ryan G. Coe

This study demonstrates a systematic methodology for establishing the design loads of a wave energy converter. The proposed design load methodology incorporates existing design guidelines, where they exist, and follows a typical design progression; namely, advancing from many, quick, order-of-magnitude accurate, conceptual stage design computations to a few, computationally intensive, high-fidelity, design validation simulations. The goal of the study is to streamline and document this process based on quantitative evaluations of the design loads’ accuracy at each design step and consideration for the computational efficiency of the entire design process. For the wave energy converter, loads, and site conditions considered, this study demonstrates an efficient and accurate methodology of evaluating the design loads.


2020 ◽  
Author(s):  
Ryan G. Coe ◽  
Giorgio Bacelli ◽  
Sterling Olson ◽  
Vincent S. Neary ◽  
Mathew B. R. Topper

While some engineering fields have benefited from systematic design optimization studies, wave energy converters have yet to successfully incorporate such analyses into practical engineering workflows. The current iterative approach to wave energy converter design leads to suboptimal solutions. This short paper presents an open-source MATLAB toolbox for performing design optimization studies on wave energy converters where power take-off behavior and realistic constraints can be easily included. This tool incorporates an adaptable control co-design approach, in that a constrained optimal controller is used to simulate device dynamics and populate an arbitrary objective function of the user's choosing. A brief explanation of the tool's structure and underlying theory is presented. In order to demonstrate the capabilities of the tool, verify its functionality, and begin to explore some basic wave energy converter design relationships, three conceptual case studies are presented. In particular, the importance of considering (and constraining) the magnitudes of device motion and forces is shown.<br>


Author(s):  
Matt Folley ◽  
Trevor Whittaker

The development of wave energy for utility-scale electricity production requires an understanding of how wave energy converters will interact with each other when part of a wave farm. Without this understanding it is difficult to calculate the energy yield from a wave farm and consequently the optimal wave farm layout and configuration cannot be determined. In addition, the uncertainty in a wave farm’s energy yield will increase the cost of finance for the project, which ultimately increases the cost of energy. Numerical modelling of wave energy converter arrays, based on potential flow, has provided some initial indications of the strength of array interactions and optimal array configurations; however, there has been limited validation of these numerical models. Moreover, the cross-validation that has been completed has been for relatively small arrays of wave energy converters. To provide some validation for large array interactions wave basin testing of three different configurations of up to 24 wave energy converters has been completed. All tests used polychromatic (irregular) sea-states, with a range of long-crested and short-crested seas, to provide validation in realistic conditions. The physical model array interactions are compared to those predicted by a numerical model and the suitability of the numerical and physical models analysed. The results are analysed at three different levels and all provide support for the cross-validation of the two models. The differences between the physical and numerical model are also identified and the implications for improving the modelling discussed.


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