Maybe less is more: Considering capacity factor, saturation, variability, and filtering effects of wave energy devices
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As with other oscillatory power conversion systems, the design of wave energy converters can be understood as an impedance matching problem. By representing the wave energy converter as a multi-port network, two separate but related impedance matching conditions can be established. Satisfying these conditions maximizes power transfer to the load. In practice, these impedance matching conditions may be used to influence the design of the system (including the hull, power take-off, controller, mooring, etc.). To this end, this paper considers some example applications of wave energy converter design with the help of the impedance matching framework.
Abstract Parametric resonance is a non‐linear phenomenon in which a system can oscillate at a frequency different from its exciting frequency. Some wave energy converters are prone to this phenomenon, which is usually detrimental to their performance. Here, a computationally efficient way of simulating parametric resonance in point absorbers is presented. The model is based on linear potential theory, so the wave forces are evaluated at the mean position of the body. However, the first‐order variation of the body's centres of gravity and buoyancy is taken into account. This gives essentially the same result as a more rigorous approach of keeping terms in the equation of motion up to second order in the body motions. The only difference from a linear model is the presence of non‐zero off‐diagonal elements in the mass matrix. The model is benchmarked against state‐of‐the‐art non‐linear Froude–Krylov and computational fluid dynamics models for free decay, regular wave, and focused wave group cases. It is shown that the simplified model is able to simulate parametric resonance in pitch to a reasonable accuracy even though no non‐linear wave forces are included. The simulation speed on a standard computer is up to two orders of magnitude faster than real time.
This paper presents an innovative wave energy conversion system that integrates an interleaved Cuk converter with advanced nonlinear control for seamless grid integration. The system efficiently extracts power on the DC side using the interleaved Cuk converter, while an inverter manages power transfer to the grid or load on the AC side. A nonlinear control architecture, based on the Lyapunov energy function, ensures stable and optimal operation under varying wave conditions, effectively addressing the challenges of variability and unpredictability inherent in wave energy. The proposed system also incorporates features to enhance power quality and minimize losses, making it a robust solution for renewable energy integration. The system's effectiveness in harnessing wave energy and achieving smooth grid integration is validated through comprehensive computer simulations in MATLAB/Simulink, with case study results demonstrating its capabilities.
This article describes the implementation of a new numerical model of the power take-off system installed in the Monterey Bay Aquarium Research Institute wave energy converter, a device developed to provide power to various oceanic research missions. The simultaneous presence of hydraulic, pneumatic, and electrical subsystems in the power take-off system represents a significant challenge in forging an accurate model able to replicate the main dynamic characteristics of the system. The validation of the new numerical model is addressed by comparing simulations with the measurements obtained during a series of bench tests. Data from the bench tests show good agreement with the numerical model. The validated model provides deeper insights into the complex nonlinear dynamics of the power take-off system and will support further performance improvements in the future.
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The development of this dataset was funded by the U.S. Department of Energy, Office of Energy Efficiency & Renewable Energy, Water Power Technologies Office to improve our understanding of the U.S. wave energy resource and to provide critical information for wave energy project development and wave energy converter design. This high resolution publicly available long-term wave hindcast dataset will - when complete - cover the entire U.S. Exclusive Economic Zone (EEZ). Available data includes the Hawaiian Islands, West and Atlantic Coasts, with future additions including the Alaskan coasts, Gulf of Mexico and the Freely associated States. The data can be used to investigate the historical record of wave statistics at any U.S. site. As such, the dataset could also be of value to any entity with marine operations inside the U.S. EEZ. These data are available for download without login credentials through the free and publicly accessible Open Energy Data Initiative (OEDI) data viewer which allows users to browse and download individual or groups of files.
The Failure Modes and Effects Analysis (FMEA) is a qualitative reliability technique for systematically analyzing each possible failure mode within a hardware system, and identifying the resulting effect on that system, the mission, and the personnel. This submission includes an updated FMEA summary for CalWave's open water demonstration including pre- and post-mitigation results, hazard identification (HAZID) analysis, and component/function rooted FMEA.
The project objectives for CalWave's deployment at PacWave are distinguished by the Preliminary Design Phase and the Detailed Design Phase. During the Preliminary Design Phase, the Risk Register was established to identify risks and mitigation strategies. The Risk Management Plan assesses potential risks of CalWave's technology and accompanying processes and describes the risk mitigation strategies for the project.
Timeseries data from the experimental testing of the OPI's prototype hydraulic drivetrain. The data is provided in .mat file format. The units for the data can be found in the ReadMe included in the submission resources.
The goal of this project is to design, fabricate, and test a hermetically sealed 50 kilowatt (kW) multistage magnetically geared generator (MGG). The Component Content Model provides data submitters with an easy and consistent means of uploading data and associated meta data about a component that is currently under development. The data fields include generic information about the component, technology classifications, current costs and performance, proposed target goals, and the environment that the component is operated in. These data are important to DOE and will be used to develop data products that provide quantitative information to guide and support programmatic decisions. Data will also be used by DOE in general assessments of MHK component readiness, performance, costs, and proposed plans. The ultimate goal is to use these data to perform research and tailor programs to best benefit the industry.
The goal of this project is to design, fabricate, and test a hermetically sealed 50 kilowatt (kW) multistage magnetically geared generator (MGG). In order to reduce risk, a sub-scale 5kW multistage MGG was first built. This project will benefit MHK device developers by providing an MHK PTO that overcomes the reliability concerns of the mechanical gears and the sizing constraints of the direct-drive generators. Measurement data for a 9.5:1 gear ratio magnetic gear with a measured peak torque of 227 N-m as well as the dual stage magnetic gear with a 63:1 gear ratio.
The goal of this project is to design, fabricate, and test a hermetically sealed 50 kilowatt (kW) multistage magnetically geared generator (MGG). This project will benefit MHK device developers by providing an MHK PTO that overcomes the reliability concerns of the mechanical gears and the sizing constraints of the direct-drive generators. Experimental Testing Data for a 6.66:1 gear ratio dual-stack magnetic gear with a measured peak torque of 1391 N-m
The goal of this project is to design, fabricate, and test a hermetically sealed 50 kilowatt (kW) multistage magnetically geared generator (MGG). In order to reduce risk, a sub-scale 5kW multistage MGG was first built. This project will benefit MHK device developers by providing an MHK PTO that overcomes the reliability concerns of the mechanical gears and the sizing constraints of the direct-drive generators. 7.67:1 gear ratio magnetic gear with a measured peak torque of 1796 N-m
This dataset contains the underwater 360-degree video files recorded with a Boxfish 360 camera in La Jolla, CA, near a gravity base anchor of the CalWave xWave wave energy converter in December 2021 over three days, at dawn, noon, and dusk. It was generated to test the ability of using this type of camera mounted on an aluminum frame as a video lander to monitor the artificial reef effect of marine energy devices and associated seafloor structures. The Boxfish 360 is made of 3 cameras each recording its own set of videos. The videos are MOV files that can be viewed individually with any video reader but need to be stitched together to create the 360-degree footage. This dataset contains all the raw video files collected at dawn, noon and dusk on 11/30/2021, 12/01/2021 and 12/02/2021, for about 1h each time. This dataset is associated with the journal manuscript below (linked in resources): Hemery, L.G.; Mackereth, K.F.; Gunn, C.M.; Pablo, E.B. Use of a 360-Degree Underwater Camera to Characterize Artificial Reef and Fish Aggregating Effects around Marine Energy Devices. J. Mar. Sci. Eng. 2022, 10, 555. https://doi.org/10.3390/jmse10050555
The ADV measurements contained in this submission were taken on the floating turbine deployment platform (TDP) located at the Memorial Bridge in Portsmouth, NH. The measurements were conducted 11/4/2021-11/9/2021 with the fastest currents occurring on 11/7/2021. Along with the submission of ADV data, a .ppt and text document further explaining the ADV deployment location is included.
CalWave / EGI's (Evergreen Innovation) TEAMER (Testing and Expertise for Marine Energy) award: data and post access report for the xWave's Real Time IMU (inertial measurement unit) Optimization for Advanced Controls.