A comprehensive time domain numerical simulation has been built for a moored, floating Oscillating Water Column (OWC) Wave Energy Converter (WEC), in order to provide accurate predictions of WEC ...power production. This novel simulation incorporates fully coupled simulations of the WEC dynamics, mooring lines, hydrodynamics, air chamber thermodynamics, air turbine dynamics and generator. It includes the forces and moments created by incoming irregular waves, moorings, buoyancy, wave radiation effects, viscous drag, and the differential pressure on the OWC hull and water column. The thermodynamics of the air chamber and the nonlinear biradial air turbine are fully coupled within the simulation.
Using a biradial air turbine with a radius and angular velocities designed to maximize mechanical power, the rated power of the PTO’s Variable Frequency Drive (VFD) and generator are optimized to maximize annual energy production. Simulations of 36 differing sea states, constituting 71% of the annual wave energy transport for a Canadian Pacific location, provide an annual power production of 530 MWhr, with an overall wave-to-wire efficiency of 11.6%. Simulation variants with no external viscous drag and linearized moorings resulted in a 42% and 16% change in energy recovered while excluding air compressibility and internal viscous drag had limited influence.
•A detailed numerical simulation of a floating mooring Oscillating Water Column.•Power production results and efficiencies for 36 differing seastates.•530 MWhr per year annual energy recovery, for a West Coast Canada deployment.•Removal of external drag and mooring linearization changed the power output.•Small changes in power output from removing air compressibility and internal drag.
•A device-agnostic classification of global wave energy resources is presented.•Classification is conducted by applying the k-means algorithm to ECMWF ERA5 data.•Six classes are returned ranging from ...enclosed seas to high energy open coasts.•Geographic and parameter space distributions match past regional scale assessments.•New devices should be optimised for moderate energy, low variability areas.
Better understanding of the global wave climate is required to inform wave energy device design and large-scale deployment. Spatial variability in the global wave climate is analysed here to provide a range of characteristic design wave climates. K-means clustering was used to split the global wave resource into 6 classes in a device agnostic, data-driven method using data from the ECMWF ERA5 reanalysis product. Classification using two sets of input data were considered: a simple set (based on significant wave height and peak wave period) and a comprehensive set including a wide range of relevant wave climate parameters. Both classifications gave resource classes with similar characteristics; 55% of tested locations were assigned to the same class. Two classes were low energy, found in enclosed seas and sheltered regions. Two classes were moderate wave energy classes; one swell dominated and the other in areas with wave action often generated by more local storms. Of the two higher energy classes; one was more often found in the northern hemisphere and the other, most energetic, predominantly on the tips of continents in the southern hemisphere. These classes match existing regional understanding of resource. Consideration of publicly available device power matrices showed good performance was primarily realised for the two highest energy resource classes (25–30% of potential deployment locations); it is suggested that effort should focus on optimising devices for additional resource classes. The authors hypothesise that the low-risk, low variability, swell dominated moderate wave energy class would be most suitable for future exploitation.
Global wave energy inventories have shown that the west coast of Canada possesses one of the most energetic wave climates in the world, with average annual wave energy transports of 40–50 kW/m ...occurring at the continental shelf. With this energetic climate, there is an opportunity to generate significant quantities of electricity from this renewable source through the use of wave energy conversion (WEC) technologies. To help evaluate the feasibility of deploying wave energy conversion technologies along the west coast of Vancouver Island, a detailed Simulating WAves Nearshore (SWAN) model was developed to assess the wave resource. The SWAN model hindcasted wave conditions along the west coast over the 2005–2012 period, at a 3 h time resolution. Detailed sensitivity studies within this report illustrate that the Fleet Numerical Meteorology and Oceanography Centre's (FNMOC) WaveWatch 3 results exhibited superior model performance when used as wave input boundary conditions. The corresponding Coupled Ocean Atmosphere Mesoscale Prediction System (COAMPS) wind fields were used as non-stationary wind forcing functions within the computational domain. Yearly and monthly mean variations of spectral and parametric wave characteristics for two reference locations were plotted to indicate both the spatial and temporal variability of the wave climate. The mean annual wave energy transport for Amphitrite Bank was calculated to be 34.5 kW/m, while the shallower second location featured 27.8 kW/m just 500 m from shore. Wave energy resources of this magnitude are not common globally and, as a consequence, signify that the west coast of Vancouver Island may be an excellent candidate location for future wave energy development.
•Nearshore wave energy resource assessment for Vancouver Island, Canada.•Unstructured SWAN model using transient wind forcing and WaveWatch 3 boundary conditions.•Utilizes new metrics for resource characterization based on IEC Technical Committee 114.•High spatial and temporal resolution investigation of two high wave energy locations.•Validated against new buoy measurement dataset on Amphitrite Bank.
•Temporal characterization of marine energy resources, at varying time scales.•Characterized wave, tidal, and ocean currents, and compared to wind and solar.•Data based exposition of grid benefits ...for wave power at high renewable scenarios.•Data based exposition of higher capacity adequacy and stability for wave power.•Detailed discussion on market implications of grid integration of marine energy.
In this paper, the applicability of marine renewable energy (MRE) for potential grid applications is presented. We show that many of the unique value streams from marine-based electricity generation resources stem from their inherent temporal characteristics, especially when compared to wind and solar. Specifically, in this work, we evaluate the timing value for three types of MRE resources: (a) tidal, (b) wave, and (c) ocean currents. First, through a suite of novel metrics, such as resource availability, persistence, and versatility, we evaluate the temporal value characteristics of these resources. Second, through a more grid-oriented numerical study, we comment on the potential ramifications of those temporal characteristics in context of energy balancing and effective load carrying capability for one marine-based resource i.e., wave. Finally, we further our understanding of the relative advantages that may be leveraged by operating wave-based generation in tandem with more established renewable resources, such as wind and solar. Our results indicate that compared to wind and solar, MRE resources are consistently more available and persistent on an hourly level throughout an entire year of operation. In addition, wave resources are also seen to reduce the balancing requirements within the power system. Our work focuses on sites specific to the United States (US) and a parallel study for a location in Great Britain (GB). Results are found to be consistent for sites in both the US and GB, implying that the grid benefits discussed in this work could apply to a number of locations globally.
Wave energy has the potential to power significant portions of economies around the world. Standard International Electrotechnical Commission methods for determining wave energy quantifies the gross ...wave resource available in the ocean, yet a significant portion of this resource is not usable by specific wave energy converters (WECs). This can provide a misleading assessment of the spatiotemporal opportunities for wave energy in deployment locations. Therefore, there is a need to develop a new technique to assess potential wave power from a device point of view that is generally applicable across WEC sizes. To address this challenge, a novel net power assessment methodology is proposed, which implements Budal’s upper bound (which describes the power available to a WEC based on its stroke), the radiation power limit (which describes the maximum radiation-based amount of wave power a WEC can absorb), and total gross incident wave power as absorbable power upper bounds. Spatiotemporal opportunities for WECs were re-evaluated based on this new technique. Numerical simulations were conducted to quantify the net wave resource available for different sized WECs (1, 2, 5, 10) at five different ocean sites in the U.S. based on wave data. The simulation results show the predicted potential wave power through the net power assessment for a 5 m device is 0.8% of the International Electrotechnical Commission assessment results at PacWave, Oregon. For the monthly average power, the results show PacWave has the most energetic wave resource (up to 406 kW in January) and WETS, Hawaii, has the steadiest wave power available (maximum COV of 0.8) among the sites. Regarding the size of the devices, results show that larger devices (e.g., 10 m) have better performance in terms of both magnitude and steadiness of power available at WETS and Los Angeles, California. Finally, the wave power potential of different sized WECs at varying locations was compared at a 3-h resolution. The maximum instantaneous power available for a 1 and 10 m device at PacWave throughout the time period was 47.8 and 3.52 × 103 kW, respectively.
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.
Marine renewable energy as a power source for ocean observation applications has the potential to allow longer deployment operations due to the consistent, higher, and denser energy available from ...this resource. This additionally could encourage deployments in remote locations where maintenance is costly or resource availability is low if dependent on solar power. More importantly, gaps in spatial data could be filled. This paper examines the feasibility of a modular horizontal pendulum wave energy converter to power National Data Buoy Center's Self‐Contained Ocean Observations Payload (SCOOP) off the coast of Washington State, U.S. The effect on power output was studied when the pendulum's radius arm, mass, and power take‐off damping were varied. Results using Matlab toolbox WEC‐Sim revealed positive correlation between radius arm length and mass to power output, where power maximised for optimal damping values. Seasonal trends in power were not significant, where a 20 kg pendulum mass was needed to meet the SCOOP base power requirement of 5 W throughout the year.
► Pellets from Pacific, Atlantic and Indian Oceans and Caribbean Sea were analyzed. ► Background concentrations from remote islands were presented. ► PCBs <10ng/g, DDTs <4ng/g, HCHs <2ng/g were ...presented as background. ► Sporadic large concentrations of POPs in the pellets were observed.
Plastic resin pellets collected from remote islands in the Pacific, Atlantic, and Indian Oceans and the Caribbean Sea were analyzed for polychlorinated biphenyls (PCBs), dichloro-diphenyltrichloroethane and its degradation products (DDTs), and hexachlorocyclohexanes (HCHs). Concentrations of PCBs (sum of 13 congeners) in the pellets were 0.1–9.9ng/g-pellet. These were 1–3 orders of magnitude smaller than those observed in pellets from industrialized coastal shores. Concentrations of DDTs in the pellets were 0.8–4.1ng/g-pellet. HCH concentrations were 0.6–1.7ng/g-pellet, except for 19.3ng/g-pellet on St. Helena, where current use of lindane is likely influence. This study provides background levels of POPs (PCBs<10ng/g-pellet, DDTs<4ng/g-pellet, HCHs<2ng/g-pellet) for International Pellet Watch. Sporadic large concentrations of POPs were found in some pellet samples from remote islands and should be considered in future assessments of pollutants on plastic debris.
Future nearshore wave energy converter (WEC) arrays will influence coastal wave and sediment dynamics, yet there are limited numerical methodologies to quantify their possible impacts. A novel ...coupled WEC-Wave numerical method was developed to quantify these possible influences on the nearshore coastal wave climate. The power performance of an Oscillating Surge Wave Energy Converter (OSWEC) array was simulated to quantify the wave energy dissipation due to the array. The OSWEC’s effect on the local wave climate was quantified by a novel coupling of two numerical models, WEC–Sim and XBeach. WEC–Sim characterizes the power extraction and wave energy transmission across the OSWEC, while XBeach captures the change in wave dynamics due to the WEC and propagates the waves to shore. This novel methodology provides the ability to directly quantify the impact of the effect of a WEC array on the local wave climate. Three case studies were analyzed to quantify the impact of a single WEC on breaking conditions and to quantify the impact of number of WECs and the array spacing on the local nearshore wave climate. Results indicate that when the WEC is placed 1100 m offshore, one WEC will cause a 1% reduction in wave height at the break point (Hsbp). As the WEC is placed further offshore, the change in Hsbp will become even smaller. Although the change in wave height from one WEC is small, WEC arrays magnify the cross–shore extent, area of influence and the magnitude of influence based on the spacing and number of WECs. For arrays with 10 or 15 WECs, the cross–shore extent was on average 200–300 m longer when the WECs were placed one to two WEC widths apart, compared with being spaced three or four widths apart. When the spacing was one WEC width apart (18 m), there was a 30% greater spatial impact on the nearshore region than arrays spaced three or four widths apart. The trend for the average transmission coefficient is within 5% for a 5, 10 or 15 WEC array, with a cumulative average of 78% transmission across all conditions.
As the wave energy sector grows and looks to the Blue Economy for commercialization opportunities, there is a distinct and pressing need to clearly understand and quantify the coupled impacts of wave ...energy converter (WEC) size and wave resource characteristics on the annual energy production, spatial variability and temporal variability. Utilizing generic frequency domain representations of the Oscilla Power Triton WEC and spectral wave conditions at PacWave (Oregon), Los Angeles (California) and WETS (Hawaii), a series of interesting results emerge. Firstly, the ‘optimal’ WEC size, from an energy standpoint, is fundamentally dependent on the frequency distribution of the incoming wave variance density spectrum. Secondly, and from a seasonality perspective, the seasonal WEC energy generation doesn’t necessarily follow the seasonal distribution of gross wave power. Finally, from an hourly power variability perspective, a reduction in WEC size generally decreases variability. However, for each of the locations investigated, there appears to be a WEC size threshold; a threshold where further reducing WEC size results in increased power variability.
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