Wave Spectral Bandwidth as a Measure of Available Wave Power

2006 ◽  
Author(s):  
George H. Smith ◽  
Vengatesan Venugopal ◽  
Jack Fasham
Keyword(s):  
Transfer Functions ◽  
Power Production ◽  
Wave Power ◽  
Wave Spectra ◽  
Energy Converter ◽  
Sea State ◽  
Spectral Moments ◽  
Constant Height ◽  
Bandwidth Parameter ◽  
Power Capture

A key requirement in the description of the performance of a wave energy converter is how the efficiency of power capture changes with the properties of the sea. This paper examines the effect of two generic power transfer functions (PTF) on power production from six simulated wave spectra. These were chosen to represent a series of wind, wind-swell mixed and swell dominated seas. The spread in energy within the sea state as defined by a variety of bandwidth parameters was examined to determine if there was a correlation between the width of the transfer function and the sea bandwidth. It was found that, for the ‘constant’ height PTF, the bandwidth parameter Bb (calculated using zeroth, minus-one and minus-two spectral moments) provided the best correlation. Customary bandwidths ε and ν performed poorly. When the PTF was allowed to vary in height as well as width there was little improvement in correlation from the un-scaled results.

scholarly journals Sea State Monitoring by Ship Motion Measurements Onboard a Research Ship in the Antarctic Waters

2021 ◽  
Vol 9 (1) ◽  
pp. 64
Author(s):  
Silvia Pennino ◽  
Antonio Angrisano ◽  
Vincenzo Della Corte ◽  
Giampaolo Ferraioli ◽  
Salvatore Gaglione ◽  
...  
Keyword(s):  
Transfer Functions ◽  
Wave Spectrum ◽  
Weather Forecast ◽  
Ship Motion ◽  
State Monitoring ◽  
Sea State ◽  
Peak Period ◽  
Research Ship ◽  
Antarctic Waters ◽  
The Antarctic

A parametric wave spectrum resembling procedure is applied to detect the sea state parameters, namely the wave peak period and significant wave height, based on the measurement and analysis of the heave and pitch motions of a vessel in a seaway, recorded by a smartphone located onboard the ship. The measurement system makes it possible to determine the heave and pitch acceleration spectra of the reference ship in the encounter frequency domain and, subsequently, the absolute sea spectra once the ship motion transfer functions are provided. The measurements have been carried out onboard the research ship “Laura Bassi”, during the oceanographic campaign in the Antarctic Ocean carried out in January and February 2020. The resembled sea spectra are compared with the weather forecast data, provided by the global-WAM (GWAM) model, in order to validate the sea spectrum resembling procedure.

Optimization of a Torus-Shaped Wave Energy Converter Attached to a Hinged Arm

2021 ◽  
Author(s):  
Mojtaba Kamarlouei ◽  
Thiago S. Hallak ◽  
Jose F. Gaspar ◽  
Miguel Calvário ◽  
C. Guedes Soares
Keyword(s):  
Genetic Algorithm ◽  
Objective Function ◽  
Wave Energy ◽  
Wave Energy Converter ◽  
Prime Mover ◽  
Optimal Result ◽  
Energy Converter ◽  
Sea State ◽  
Absorbed Power ◽  
Spring System

Abstract This paper presents the adaptation of a torus wave energy converter prime mover to an onshore or nearshore fixed platform, by a hinged arm. An optimization code is developed to obtain the best torus and arm geometry, as well as the power take-off parameters, taking as objective function the maximization of total wave absorbed power. In this paper, the power take-off system is modelled as a simplified damper and spring system, where the parameters are optimized for the phase control of the wave energy converter in each sea state, whereas the optimization process is performed with a genetic algorithm. Finally, the optimal result for the productive sea state indicates that the absorbed power is relatively considerable while a better survivability performance is expected from a torus wave energy converter compared to a conventional truncated prime mover.

scholarly journals Validation of a CFD-based numerical wave tank model for the power production assessment of the wavestar ocean wave energy converter

2020 ◽  
Vol 146 ◽  
pp. 2499-2516 ◽  
Author(s):  
Christian Windt ◽  
Josh Davidson ◽  
Edward J. Ransley ◽  
Deborah Greaves ◽  
Morten Jakobsen ◽  
...  
Keyword(s):  
Wave Energy ◽  
Power Production ◽  
Wave Energy Converter ◽  
Ocean Wave ◽  
Numerical Wave Tank ◽  
Energy Converter ◽  
Tank Model ◽  
Wave Tank ◽  
Ocean Wave Energy ◽  
Numerical Wave

Impact of the Uncertainties of the RAOs of a Semisubmersible Platform on the Performance of a Motion-Based Wave Inference Method

2019 ◽  
Author(s):  
J. Mas-Soler ◽  
Pedro C. de Mello ◽  
Eduardo A. Tannuri ◽  
Alexandre N. Simos ◽  
A. Souto-Iglesias
Keyword(s):  
Bayesian Inference ◽  
Transfer Functions ◽  
Inference Model ◽  
Sea State ◽  
Statistical Errors ◽  
Regularization Parameters ◽  
Ill Posed ◽  
State Estimations ◽  
The Impact ◽  
Mathematical Process

Abstract Motion based wave inference allows the estimation of the directional sea spectrum from the measured motions of a vessel. Solving the resulting inverse problem is challenging as it is often ill-posed; as a matter of fact, statistical errors of the estimated platform response functions (RAOs) may lead to misleading estimations of the sea states as many noise values are severely amplified in the mathematical process. Hence, in order to obtain reliable estimations of the sea conditions some hypothesis must be included by means of regularization parameters. This work discusses how these errors affect the regularization parameters and the accuracy of the sea state estimations. For this purpose, a statistical quantification of the errors associated to the estimated transfer functions has been included in an expanded Bayesian inference approach. Then, the resulting statistical inference model has been verified by means of a comparison between the outputs of this approach and those obtained without considering the statistical errors in the Bayesian inference. The assessment of the impact on the accuracy of the estimations is based on the results of a dedicated model-scale experimental campaign, which includes more than 150 different test conditions.

scholarly journals Characterization of Extreme Wave Conditions for Wave Energy Converter Design and Project Risk Assessment

2020 ◽  
Vol 8 (4) ◽  
pp. 289 ◽  
Author(s):  
Vincent S. Neary ◽  
Seongho Ahn ◽  
Bibiana E. Seng ◽  
Mohammad Nabi Allahdadi ◽  
Taiping Wang ◽  
...  
Keyword(s):  
Return Period ◽  
Wave Energy ◽  
Wave Energy Converter ◽  
Extreme Value Analysis ◽  
Extreme Wave ◽  
Energy Converter ◽  
Sea State ◽  
Value Analysis ◽  
Wave Conditions ◽  
Wave Models

Best practices and international standards for determining n-year return period extreme wave (sea states) conditions allow wave energy converter designers and project developers the option to apply simple univariate or more complex bivariate extreme value analysis methods. The present study compares extreme sea state estimates derived from univariate and bivariate methods and investigates the performance of spectral wave models for predicting extreme sea states at buoy locations within several regional wave climates along the US East and West Coasts. Two common third-generation spectral wave models are evaluated, a WAVEWATCH III® model with a grid resolution of 4 arc-minutes (6–7 km), and a Simulating WAves Nearshore model, with a coastal resolution of 200–300 m. Both models are used to generate multi-year hindcasts, from which extreme sea state statistics used for wave conditions characterization can be derived and compared to those based on in-situ observations at National Data Buoy Center stations. Comparison of results using different univariate and bivariate methods from the same data source indicates reasonable agreement on average. Discrepancies are predominantly random. Large discrepancies are common and increase with return period. There is a systematic underbias for extreme significant wave heights derived from model hindcasts compared to those derived from buoy measurements. This underbias is dependent on model spatial resolution. However, simple linear corrections can effectively compensate for this bias. A similar approach is not possible for correcting model-derived environmental contours, but other methods, e.g., machine learning, should be explored.

Experimental Study on Model Predictive Control for a Point Absorber Type Wave Energy Converter With a Linear Generator

2018 ◽  
Author(s):  
Jun Umeda ◽  
Hiroki Goto ◽  
Toshifumi Fujiwara ◽  
Tomoki Taniguchi ◽  
Shunji Inoue
Keyword(s):  
Predictive Control ◽  
Wave Energy ◽  
Spectral Distribution ◽  
Time Horizon ◽  
Production Efficiency ◽  
Power Production ◽  
Irregular Waves ◽  
Regular Waves ◽  
Energy Converter ◽  
Point Absorber

This paper presents the experimental evaluation results of power production efficiency of model predictive control (MPC) on a wave energy converter (WEC) with a linear generator in regular and irregular waves. A bottom-fixed WEC of point absorber type was subjected to the WEC model in this paper. To compare the power production efficiency, the power production efficiency of the approximate complex-conjugate control with considering the copper loss (ACL) was also evaluated. In regular waves, the MPC performance was comparable to the ACL one in the power-production amount reasonably. In irregular waves which have narrow band spectral distribution, a same trend as the trend in regular waves was obtained. On the other hand, in irregular waves which have broadband spectral distribution, the MPC was more effective than the ACL. Moreover, Experiments in regular and irregular waves were carried out in the MPC under the constraint of the small heave displacement. The constraint of the displacement was approximately satisfied by the MPC. This is useful in practical operation. It is also investigated experimentally how time horizon affects the performance of the MPC. When the time horizon is short, the power production amount of the MPC increases.

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