The floating oscillating surge wave energy converter (FOSWEC) is a wave energy converter that was designed, built, and tested to develop an open-access data set for the purpose of numerical model validation. Here, this paper details the experimental testing of the 1:33-scale FOSWEC in a directional wave basin, and compares experimental data to numerical simulations using the wave energy converter simulator (WEC-Sim) open-source code. The FOSWEC consists of a floating platform moving in heave, pitch, and surge, and two pitching flaps. Power is extracted through relative motion between each of the flaps and the platform. The device was designed to constrain different degrees of freedom so that it could be configured into a variety of operating conditions with varying dynamics. The FOSWEC was tested in a range of different conditions including: static offset, free decay, forced oscillation, wave excitation, and dynamic response to regular waves. In this paper, results from the range of experimental tests are presented and compared to numerical simulations using the WEC-Sim code.
The International Energy Agency Technology Collaboration Programme for Ocean Energy Systems (OES) initiated the OES Wave Energy Conversion Modelling Task, which focused on the verification and validation of numerical models for simulating wave energy converters (WECs). The long-term goal is to assess the accuracy of and establish confidence in the use of numerical models used in design as well as power performance assessment of WECs. To establish this confidence, the authors used different existing computational modelling tools to simulate given tasks to identify uncertainties related to simulation methodologies: (i) linear potential flow methods; (ii) weakly nonlinear Froude–Krylov methods; and (iii) fully nonlinear methods (fully nonlinear potential flow and Navier–Stokes models). This article summarizes the code-to-code task and code-to-experiment task that have been performed so far in this project, with a focus on investigating the impact of different levels of nonlinearities in the numerical models. Two different WECs were studied and simulated. The first was a heaving semi-submerged sphere, where free-decay tests and both regular and irregular wave cases were investigated in a code-to-code comparison. The second case was a heaving float corresponding to a physical model tested in a wave tank. We considered radiation, diffraction, and regular wave cases and compared quantities, such as the WEC motion, power output and hydrodynamic loading.
NoiseSpotter is currently designed for a 2-week deployment. This timeline will likely be problematic for MHK developers. Developers will want a robust/proven system that they can deploy and not worry about for longer than 2 weeks (especially for the continued monitoring of a site).
This paper details the development and validation of a numerical model of the Wavestar wave energy converter (WEC) developed in WEC-Sim. This numerical model was developed in support of the WEC Control Competition (WECCCOMP), a competition with the objective of maximizing WEC performance over costs through innovative control strategies. WECCCOMP has two stages: numerical implementation of control strategies, and experimental implementation. The work presented in this paper is for support of the numerical implementation, where contestants are provided a WEC-Sim model of the 1:20 scale Wavestar device to develop their control algorithms. This paper details the development of the numerical model in WEC-Sim and of its validation through comparison to experimental data.
Ruehl, Kelley; Chang, G.; Jones, C.A.; Roberts, J.; Chartrand, C.
Modeled nearshore wave propagation was investigated downstream of simulated wave energy converters (WECs) to evaluate overall near- and far-field effects of WEC arrays. Model sensitivity to WEC characteristics and WEC array deployment scenarios was evaluated using a modified version of an industry standard wave model, Simulating WAves Nearshore (SWAN), which allows the incorporation of device-specific WEC characteristics to specify obstacle transmission. The sensitivity study illustrated that WEC device type and subsequently its size directly resulted in wave height variations in the lee of the WEC array. Wave heights decreased up to 30% between modeled scenarios with and without WECs for large arrays (100 devices) of relatively sizable devices (26 m in diameter) with peak power generation near to the modeled incident wave height. Other WEC types resulted in less than 15% differences in modeled wave height with and without WECs, with lesser influence for WECs less than 10 m in diameter. Wave directions and periods were largely insensitive to changes in parameters. However, additional model parameterization and analysis are required to fully explore the model sensitivity of peak wave period and mean wave direction to the varying of the parameters.