Ringwood, John V.; Tom, Nathan; Ferri, Francesco; Yu, Yi H.; Coe, Ryan G.; Ruehl, Kelley M.; Bacelli, Giorgio; Shi, Shuo; Patton, Ron J.; Tona, Paolino; Sabiron, Guillaume; Merigaud, Alexis; Ling, Bradley A.; Faedo, Nicolas
The wave energy control competition established a benchmark problem which was offered as an open challenge to the wave energy system control community. The competition had two stages: In the first stage, competitors used a standard wave energy simulation platform (WEC-Sim) to evaluate their controllers while, in the second stage, competitors were invited to test their controllers in a real-time implementation on a prototype system in a wave tank. The performance function used was based on converted energy across a range of standard sea states, but also included aspects related to economic performance, such as peak/average power, peak force, etc. This paper compares simulated and experimental results and, in particular, examines if the results obtained in a linear system simulation are borne out in reality. Overall, within the scope of the device tested, the range of sea states employed, and the performance metric used, the conclusion is that high-performance WEC controllers work well in practice, with good carry-over from simulation to experimentation. However, the availability of a good WEC mathematical model is deemed to be crucial.
The U.S. Department of Energy (DOE) Water Power Technologies Office’s (WPTO) initial investment in marine energy software was driven by needs identified over a decade ago. WPTO-funded research was first launched because of a U.S. congressional mandate that called for the DOE to officially research marine energy technologies, which also established the DOE WPTO in 2008. A congressional mandate requested the WPTO to evaluate a variety of marine energy devices, establish baseline levelized cost of energy estimates, and provide an overall report to Congress. This congressional mandate led to the Reference Model Project (RMP), for which WPTO funded a national multi-laboratory team to develop these reference models, based on state-of-the-art designs of six marine energy converter archetypes that consisted of three current energy converters and three wave energy converters (WEC). Each device was designed to operate for a specific marine resource, thus allowing the devices to serve as reference models for future studies. The RMP congressional report cited the need for improved marine energy software to handle a variety of device designs, as well as a need to standardize performance outputs. Without validated software packages and established metrics, information presented to the WPTO by technology developers could be incorrect or inaccurate and result in misleading conclusions. The recommendation to coordinate WPTO investment in software for numerical modeling and analysis was given a high priority because it would directly fill needs at the time, and focused funding would amplify impact. By sponsoring software development, WPTO would provide industry developers, university researchers, and national laboratories software that could be used, customized, and advanced, thus supporting the overall advancement of marine energy.
This paper focuses on the role of the Marine Renewable Energy (MRE) Software Knowledge Hub on the Portal and Repository for Information on Marine Renewable Energy (PRIMRE). The MRE Software Knowledge Hub provides online services for MRE software users and developers, and seeks to develop assessments and recommendations for improving MRE software in the future. Online software discovery platforms, known as the Code Hub and the Code Catalog, are provided. The Code Hub is a collection of open-source MRE software that includes a landing page with search functionality, linked to files hosted on the MRE Code Hub GitHub organization. The Code Catalog is a searchable online platform for discovery of useful (open-source or commercial) software packages, tools, codes, and other software products. To gather information about the existing MRE software landscape, a software survey is being performed, the preliminary results of which are presented herein. Initially, the data collected in the MRE software survey will be used to populate the MRE Software knowledge hub on PRIMRE, and future work will use data from the survey to perform a gap analysis and develop a vision for future software development. Additionally, as one of PRIMRE’s roles is to support development of MRE software within project partners, a silo of knowledge relating to best practices has been gathered. An early draft of new guidance developed from this knowledge is presented.
The ability to handle data is critical at all stages of marine energy development. The Marine and Hydrokinetic Toolkit (MHKiT) is an open-source marine energy software, which includes modules for ingesting, applying quality control, processing, visualizing, and managing data. MHKiT-Python and MHKiT-MATLAB provide robust and verified functions that are needed by the marine energy community to standardize data processing. Calculations and visualizations adhere to International Electrotechnical Commission technical specifications and other guidelines. A resource assessment of National Data Buoy Center buoy 46050 near PACWAVE is performed using MHKiT and we discuss comparisons to the resource assessment provided performed by Dunkle et al. (2020).
This paper focuses on the role of the Marine Renewable Energy (MRE) Software Knowledge Hub on the Portal and Repository for Information on Marine Renewable Energy (PRIMRE). The MRE Software Knowledge Hub provides online services for MRE software users and developers, and seeks to develop assessments and recommendations for improving MRE software in the future. Online software discovery platforms, known as the Code Hub and the Code Catalog, are provided. The Code Hub is a collection of open-source MRE software that includes a landing page with search functionality, linked to files hosted on the MRE Code Hub GitHub organization. The Code Catalog is a searchable online platform for discovery of useful (open-source or commercial) software packages, tools, codes, and other software products. To gather information about the existing MRE software landscape, a software survey is being performed, the preliminary results of which are presented herein. Initially, the data collected in the MRE software survey will be used to populate the MRE Software knowledge hub on PRIMRE, and future work will use data from the survey to perform a gap analysis and develop a vision for future software development. Additionally, as one of PRIMRE’s roles is to support development of MRE software within project partners, a silo of knowledge relating to best practices has been gathered. An early draft of new guidance developed from this knowledge is presented.
Faraggiana, E.; Whitlam, C.; Chapman, J.; Hillis, A.; Roesner, J.; Hann, M.; Greaves, D.; Yu, Y.H.; Ruehl, Kelley M.; Masters, I.; Foster, G.; Stockman, G.
A submerged wave device generates energy from the relative motion of floating bodies. In WaveSub, three floats are joined to a reactor; each connected to a spring and generator. Electricity generated damps the orbital movements of the floats. The forces are non-linear and each float interacts with the others. Tuning to the wave climate is achieved by changing the line lengths, so there is a need to understand the performance trade-offs for a large number of configurations. This requires an efficient, large displacement, multidirectional, multi-body numerical scheme. Results from a 1/25 scale wave basin experiment are described. Here, we show that a time domain linear potential flow formulation (Nemoh, WEC-Sim) can match the tank testing provided that suitably tuned drag coefficients are employed. Inviscid linear potential models can match some wave device experiments; however, additional viscous terms generally provide better accuracy. Scale experiments are also prone to mechanical friction, and we estimate friction terms to improve the correlation further. The resulting error in mean power between numerical and physical models is approximately 10%. Predicted device movement shows a good match. Overall, drag terms in time domain wave energy modelling will improve simulation accuracy in wave renewable energy device design.
This numerical study compares thewave field generated by the spectral wave action balance code, SNL-SWAN, to the linear-wave boundary-element method (BEM) code, WAMIT. The objective of this study is to assess the performance of SNL-SWAN for modeling wave field effects produced by individual wave energy converters (WECs) and wave farms comprising multiple WECs by comparing results from SNL-SWAN with those produced by the BEM codeWAMIT. BEM codes better model the physics of wave-body interactions and thus simulate a more accurate near-field wave field than spectral codes. In SNL-SWAN, the wave field's energy extraction is modeled parametrically based on the WEC's power curve. The comparison between SNL-SWAN andWAMIT is made over a range of incident wave conditions, including short-, medium-, and long-wavelength waves with various amounts of directional spreading, and for three WEC archetypes: a point absorber (PA), a pitching flap (PF) terminator, and a hinged raft (HR) attenuator. Individual WECs and wave farms of five WECs in various configuration were studied with qualitative comparisons made of wave height and spectra at specific locations, and quantitative comparisons of the wave fields over circular arcs around the WECs as a function of radial distance. Results from this numerical study demonstrate that in the near-field, the difference between SNL-SWAN andWAMIT is relatively large (between 20% and 50%), but in the far-field from the array the differences are minimal (between 1% and 5%). The resultant wave field generated by the two different numerical approaches is highly dependent on parameters such as: directional wave spreading, wave reflection or scattering, and the WEC's power curve.
A passive yaw implementation is developed, validated, and explored for the WEC-Sim, an open-source wave energy converter modeling tool that works within MATLAB/Simulink. The Reference Model 5 (RM5) is selected for this investigation, and a WEC-Sim model of the device is modified to allow yaw motion. A boundary element method (BEM) code was used to calculate the excitation force coefficients for a range of wave headings. An algorithm was implemented in WEC-Sim to determine the equivalent wave heading from a body's instantaneous yaw angle and interpolate the appropriate excitation coefficients to ensure the correct time-domain excitation force. This approach is able to determine excitation force for a body undergoing large yaw displacement. For the mathematically simple case of regular wave excitation, the dynamic equation was integrated numerically and found to closely approximate the results from this implementation in WEC-Sim. A case study is presented for the same device in irregular waves. In this case, computation time is increased by 32x when this interpolation is performed at every time step. To reduce this expense, a threshold yaw displacement can be set to reduce the number of interpolations performed. A threshold of 0.01o was found to increase computation time by only 22x without significantly affecting time domain results. Similar amplitude spectra for yaw force and displacements are observed for all threshold values less than 1o, for which computation time is only increased by 2.2x.
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 M.; 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.
The WEC-Sim project is currently on track, having met both the SNL and NREL FY14 Milestones, as shown in Table 1 and Table 2. This is also reflected in the Gantt chart uploaded to the WEC-Sim SharePoint site in the FY14 Q4 Deliverables folder. The work completed in FY14 includes code verification through code-to-code comparison (FY14 Q1 and Q2), preliminary code validation through comparison to experimental data (FY14 Q2 and Q3), presentation and publication of the WEC-Sim project at OMAE 2014 [1], [2], [3] and GMREC/METS 2014 [4] (FY14 Q3), WEC-Sim code development and public open-source release (FY14 Q3), and development of a preliminary WEC-Sim validation test plan (FY14 Q4). This report presents the preliminary Validation Testing Plan developed in FY14 Q4. The validation test effort started in FY14 Q4 and will go on through FY15. Thus far the team has developed a device selection method, selected a device, and placed a contract with the testing facility, established several collaborations including industry contacts, and have working ideas on the testing details such as scaling, device design, and test conditions.
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.