Modeling and validation of a small heave plate wave energy converter

Ocean waves are a consistent, reliable source of renewable energy, but major hurdles still exist before wave energy will be a viable grid power source. Several applications exist today that would benefit from a small stand-alone wave energy system. The goal of this project was to design, build and test a small wave energy converter to operate in the waters adjacent to the U.S. Naval Academy in Annapolis, MD, producing 50W average power. The result was a cylindrical heaving device with integrated oscillating water column, with outer diameter of 3.4 ft and total weight of 94.5 lbs. The design utilizes off-the-shelf components and 3D printed parts to minimize cost. Follow-on testing (both tank and field) will be conducted to evaluate performance of the concept design. This project serves as a foundation for future wave energy research and design projects.

Marine energy (ME) has the potential to power businesses in the blue economy. Kelp farms are an emerging maritime market of the blue economy and are predicted to grow, but they are not currently using ME for their power needs. As the number and size of kelp farms increase, more offshore power will be needed onsite for operations, monitoring, and harvesting. ME devices such as tidal current energy converters and wave energy converters (WECs) may be used to supply power for these needs. This article assesses the status of kelp farming in the continental United States, investigates the electricity needs of kelp farms, and examinesthe feasibility of generating the required electricity from wave and tidal current energy. The United States currently has 165 kelp farms that have either active or pending permits. The farms use electricity for boat operations, kelp drying, environmental monitoring, offshore lighting, and the raising and lowering of lines. Most kelp farms are in protected, nearshore waters that do not have significant wave energy resources. The limited available wave energy could be used to power small devices, but WECs have not yet been developed for that application. Some kelp farms are in locations that feature significant tidal energy resources, but small tidal current energy converters that are compatible with existing farm operations are not yet commercially available. As low-power WECs and tidal current energy converters are developed, kelp farms could be research partners and early adopters of the new technologies, which would encourage their broader use by other blue economy businesses.

Current global concerns on environmental protection and sustainable development for clean energy have led to the creation of new engineering devices. These technologies reduce harmful greenhouse gas emissions in the atmosphere, global warming and reduce dependence on fossil fuels to produce energy. Many countries are now moving towards strategies to achieve maximum power available from the factory to reduce greenhouse gas emissions are concentrated. Wave energy is an emerging technology that is currently under research and development is considerable. Wave energy is essentially an indirect form of solar energy. There is a long maritime border in the south and north of the country, Iran's potential to absorb the energy of the sea talk show. In this thesis, the energy in waves of Iranian ports to use wave energy absorber is investigated, and an experimental model of wave energy converter designed, manufactured and tested in regular waves and it has been analyzed.

Dynamic Wave Energy Converter (WEC) models utilize a wide variety of fundamental hydrodynamic theories. When incorporating novel hydrodynamic theories into numerical models, there are distinct impacts on WEC rigid body motions, cable dynamics, and final power production. This paper focuses on developing an understanding of the influence several refined hydrodynamic theories have on WEC dynamics, including weakly nonlinear Froude-Krylov and hydrostatic forces, body-to-body interactions, and dynamic cable modelling. All theories have evolved from simpler approaches and are of importance to a wide array of WEC archetypes. This study quantifies the impact these theories have on modelling accuracy through a WEC case study. Theoretical differences are first explored in a regular sea state. Subsequently, numerical validation efforts are performed against field data following wave reconstruction techniques. Comparisons of significance are WEC motion and cable tension. It is shown that weakly nonlinear Froude-Krylov and hydrostatic force calculations and dynamic cable modelling both significantly improve simulated WEC dynamics. However, body-to-body interactions are not found to impact simulated WEC dynamics.

Ocean wave energy has not yet gained popularity as a renewable energy source because of intermittent nature of available wave power. Still deriving a constant power at the output, requires embedding of energy storage devices of sufficient capacity into the wave energy converter. A Permanent Magnet Synchronous Generator(PMSG) based adjustable speed energy extracting scheme is employed so as to operate the air-turbine close to its Maximum Power Point operation. The variable voltage variable frequency AC supply generated by the PMSG is processed by a diode bridge- VSI cascade, to generate usable regulated AC supply. In order to estimate the energy storage requirement, especially under different climatic conditions, the emulation of the DC bus voltage dynamics is required. Considering typical wave height, wave period and differential pressure/ wave power variation applicable to the site of Indian wave energy plant, off-line computation of the DC bus voltage dynamics is carried out using MATLAB based transient model of the complete wave energy converter. Finally, the results obtained from the emulation carried out employing micro-controller P89V51RD2 are given.

Development of wave energy conversion systems may yield many key benefits for society such as the production of electrical power or fresh water for remote communities. However, complex ocean dynamics make it difficult for technology developers to not only address the stability and survivability of their systems, but also to establish energy conversion rates that are fundamental to proving economic viability. Building physical prototypes presents many challenges in terms of cost, accessible facilities, and time requirements. The use of accurate numerical modelling and computer simulation can help guide design and significantly reduce the number of physical prototype tests required and as a result play a primary role in the development of wave energy conversion systems that have to operate in challenging marine environments. SurfPower is an ocean wave energy converter (WEC) that converts wave motion into useful energy through surge and heave motion of a point absorber. The system pumps seawater into a high pressure hydraulic network that generates electricity via a turbine or freshwater via desalination at a facility onshore. The system is nonlinear due to the significant change in draft and mooring reaction load through the energy capture cycle of the device. This makes the use of nonlinear time domain simulation ideal for analysis and design of the system. Furthermore, utilizing a simplified nonlinear hydrodynamic model available in the time domain results in a practical early-stage design tool for system refinement. The focus of this work is to compare the results of scale model testing completed at the Institute for Ocean Technology in St. John’s, Newfoundland, with results produced from an equivalent system simulated in the time domain simulation software ProteusDS. The results give an assessment of the range of error that can be used to assess other experiments of the SurfPower WEC at full scale.

Wave energy fluctuating a great deal endangers the security of power grid especially micro grid in island. A DC nano grid supported by batteries is proposed to smooth the output power of wave energy converters (WECs). Thus, renewable energy converters connected to DC grid is a new subject. The characteristics of WECs are very important to the connection technology of HPTO type WECs and DC nano grid. Hydraulic power take-off system (HPTO) is the core unit of the largest category of WECs, with the functions of supplying suitable damping for a WEC to absorb wave energy, and converting captured wave energy to electricity. The HPTO is divided into a hydraulic energy storage system (HESS) and a hydraulic power generation system (HPGS). A primary numerical model for the HPGS is established in this paper. Three important basic characteristics of the HPGS are deduced, which reveal how the generator load determines the HPGS rotation rate. Therefore, the connector of HPTO type WEC and DC nano grid would be an uncontrollable rectifier with high reliability, also would be a controllable power converter with high efficiency, such as interleaved boost converter-IBC. The research shows that it is very flexible to connect to DC nano grid for WECs, but bypass resistance loads are indispensable for the security of WECs.

<p indent="0mm">The special cape-shaped topography of a headland sandy bay is the reason its shoreline varies differently than that of a straight-line coast. The Narrabeen embayment is located on the southeastern coastline of Australia approximately <sc>20 km</sc> north of Sydney. The enclosed sandy beach is <sc>3.6 km</sc> in length and is composed of fine to medium quartz sand overlying sandstone bedrock, with a median sand grain size D₅₀ of <sc>0.3 mm.</sc> Due to the prevalence of moderate to high wave energy conditions and the exposure of the central and northern portions of the beach to the prevailing south-southeastern swell waves. The morphodynamic responses of the Narrabeen beach are highly variable and rapid alongshore. The beach state was predominantly influenced by episodic storm events throughout the year when erosion and accretion can occur. This study analyzed measurements of cross-shore profiles of the Narrabeen headland sandy bay from 1997-1998. With reference to an atypical huge-wave event, this paper describes in detail the beach erosion caused by huge-waves and the beach restoration caused by small waves after the huge-wave event. It also details the relationship between shoreline variation and wave parameters (wave height and wave angle). To discuss the regulations and causes of beach rotation, the study selected six huge wave events that occurred in 1990–2000, all of which were followed by over eight months of small waves, and analyzed the alongshore variation. The results show that the morphodynamic responses of the Narrabeen beach are highly variable and rapid alongshore. During the huge wave events, the beach was eroded and the shoreline retreated. In the aftermath, the small waves restored the beach. The difference in the shoreline variation due to small waves exhibits a rotational pattern. Wave height is related to sand volume above mean sea level and sand accumulation was rapid and high after the big nearshore wave events. The Southern Oscillation Index (SOI) is closely related to the variability in the shoreline. Time-lagged cross-correlations between monthly beach shoreline positions and the SOI were calculated to investigate the presence of stronger cross-correlations between the beach shoreline and the SOI; the central profile (profile 4) is the most sensitive to the feedback of SOI change. The small waves after a huge-wave event make beach rotation periodic. Analysis of directional wave data and the SOI suggests that beach change is driven by changes in wave height (power) and a subtle change in wave direction, both of which are positively related to the SOl. The change in the SOI induces changes in the wave angles, which leads to sediment transport. This is the most important factor in beach rotation. These results reconfirm huge-wave and small waves subaerial morphology, in particular, these results confirm that the wave height and angle, which are induced by the SOI after a huge-wave event, are key drivers of alongshore variation in headland sandy bay coastlines. Under small wave conditions, the northern and mid beach profiles have negative correlations with SOI index, while the southern beach profiles have positive correlations with SOI index. This lead to sediment erosion in the north while sediment deposition in the south. And the shoreline thereby shows a rotational pattern. With the variation of the SOI index, the sediment movement changes in each beach profile, and the shoreline's rotational pattern shows periodicity.

Hydrodynamic numerical models of Wave Energy Converters (WEC) contain hydrodynamic coefficients that are commonly obtained from numerical codes that solve linear potential flow problems using Boundary Element Methods (BEM codes). The assumptions made by the BEM codes in their calculation of the linear hydrodynamic coefficients are violated by the large and nonlinear motions that wave activation body class WECs often go through during operation. In this study, Forced Oscillation Tests were used to evaluate the hydrodynamic torque coefficients estimated for an Oscillating Wave Surge Converter (OWSC) WEC by two BEM codes; WAMIT and Nemoh. The paper describes the tests and the active Force Feedback Dynamometer test rig used to perform them. The results indicate good agreement between the BEM codes and experimental data for small angular displacement amplitude oscillations, as expected; up to 0.3 rad. The torque not predicted by the BEM codes is presented and shown to have an amplitude and phase that vary throughout the range of tests performed.

Modelling and design of a perfectly-absorbing wave energy converter

Disruption to benthic habitats by moorings of wave energy installations: A modelling case study and implications for overall ecosystem functioning

This paper presents a numerical investigation on the interaction between focused waves and wave energy converter (WEC) models using a hybrid solver, qaleFOAM, which couples a two-phase incompressible Navier–Stokes (NS) solver OpenFOAM/InterDyMFoam with the quasi Lagrangian–Eulerian finite element method (QALE-FEM) based on the fully non-linear potential theory (FNPT) using the domain-decomposition approach. In the qaleFOAM, the NS solver deals with a small region near the structures (NS domain), where the viscous effect may be significant; the QALE-FEM covers the remaining computational domain (FNPT domain); an overlap (transitional) zone is applied between two domains. The WEC models, mooring system and the wave conditions are given by the Collaborative Computational Project in Wave–Structure Interaction (CCP-WSI) Blind Test Series 2. In the numerical simulation, the incident wave is generated in the FNPT domain using a self-correction wavemaker and propagates into the NS domain through the coupling boundaries and attached transitional zones. An improved passive wave absorber is imposed at the outlet of the NS domain for wave absorption. The practical performance of the qaleFOAM is demonstrated by comparing its prediction with the experimental data, including the wave elevation, motion responses (surge, heave and pitch) and mooring load.

Ocean energy technologies are in their developmental stages, like other renewable energy sources. To be useable in the energy market, most components of wave energy devices require further improvement. Additionally, wave resource characteristics must be evaluated and estimated correctly to assess the wave energy potential in various coastal areas. Multiple algorithms integrated with numerical models have recently been developed and utilized to estimate, predict, and forecast wave characteristics and wave energy resources. Each algorithm is vital in designing wave energy converters (WECs) to harvest more energy. Although several algorithms based on optimization approaches have been developed for efficiently designing WECs, they are unreliable and suffer from high computational costs. To this end, novel algorithms incorporating machine learning and deep learning have been presented to forecast wave energy resources and optimize WEC design. This review aims to classify and discuss the key characteristics of machine learning and deep learning algorithms that apply to wave energy forecast and optimal configuration of WECs. Consequently, in terms of convergence rate, combining optimization methods, machine learning, and deep learning algorithms can improve the WECs configuration and wave characteristic forecasting and optimization. In addition, the high capability of learning algorithms for forecasting wave resource and energy characteristics was emphasized. Moreover, a review of power take-off (PTO) coefficients and the control of WECs demonstrated the indispensable ability of learning algorithms to optimize PTO parameters and the design of WECs.

Effect of compression on wave diffraction by a floating elastic plate

Advanced wave energy conversion technologies for sustainable and smart sea: A comprehensive review