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At least 145 records · Page 8

Abundances and Transients from Neutron Star–White Dwarf Mergers

Abstract We systematically investigate the mergers of neutron star–white dwarf binaries from beginning to end, with a focus on the properties of the inflows and outflows in accretion disks and their electromagnetic emissions. Using population synthesis models, we determine a subset of these binaries in which the white dwarf companion undergoes unstable mass transfer and complete tidal disruption, forming a large accretion disk around the neutron star. The material evolves according to a one-dimensional advection-dominated accretion-disk model with nuclear burning, neutrino emissions, and disk-surface wind ejection. The extreme dynamics of the entire process have proven difficult to analyze, and thus currently, the properties are poorly understood. The outflows from the mergers are iron- and nickel-rich, giving rise to optical and infrared emissions powered by the decay of the radioactive iron-type isotopes, calculated via the SuperNu light-curve code. We find these systems capable of powering bright, yet short-lived, optical transients with the potential to power gamma-ray bursts.

79 ASTRONOMY AND ASTROPHYSICS↗

Reference Site Condition Datasets for Floating Wind Arrays in the United States

Floating offshore wind farm design is highly site-specific, requiring detailed information about the specific conditions of a project area for realistic design studies. Unfortunately, publicly available site condition data for potential floating offshore wind project sites in the United States is scarce. To support U.S. offshore wind research, we developed reference site condition datasets, including metocean and seabed information, for four potential floating wind project areas in the U.S.: Humboldt Bay, Morro Bay, the Gulf of Maine, and the Gulf of Mexico. These datasets were compiled using publicly available data. Our metocean analysis, covering wind, waves, and surface currents, utilized measurement data from 2000 to 2020. Sources included the National Renewable Energy Laboratory’s National Offshore Wind Dataset for wind data, National Data Buoy Center buoys for wave data, and the High Frequency Radar Network for surface currents. These data were integrated into hourly time series used to compute extreme return periods up to 500 years, monthly statistics, and joint probability clusters for fatigue analysis. Soil conditions were evaluated using the usSEABED database and bathymetry grids were interpolated from the NCEI Digital Elevation Model Global Mosaic. Further information on the datasets and how they were created can be found in: Biglu, M., M. Hall, E. Lozon, S. Housner. 2024. Reference Site Conditions for Floating Wind Arrays in the United States. Golden, CO: National Renewable Energy Laboratory (NREL). NREL/TP-5000-89897. The data are also available at: https://github.com/FloatingArrayDesign/SiteConditions The content of each dataset is as follows: _NOW23_wind.txt: Hourly NOW-23 wind data up to a height of 400 meter. _metocean_1hr.txt: Hourly time series including wind, wave, surface current and temperature data. _Summary.xlsx: Metocean data, including extreme values, joint probability distributions and monthly statistics. _usSEABED_soil.csv: Extract of the usSEABED database for this specific site. _bathymetry_200m.txt (and 500m, 1000m): Gridded seabed depth data.

16 TIDAL AND WAVE POWER↗

Near wake evolution of a tidal stream turbine due to asymmetric sheared turbulent inflow with different integral length scales

Tidal stream turbines deployed at highly energetic open water sites are subjected to sheared inflow in the rotor plane. The inflow shear is expected to cause asymmetric loading on the rotor blades and affect the downstream wake. In the current study, two different turbulent inflow conditions, static-high shear and dynamic shear, were generated via an active-grid turbulence generator. A 1:20 scaled three-bladed horizontal axis tidal turbine model was tested in those conditions. The results were compared to a quasi-laminar case with no imposed turbulence or shear. The results show that the high shear reduces the average performance, with a drop of up to 16% in the optimal power coefficient. Besides, the shear profiles increase torque fluctuations and induce significant differences in wake hydrodynamics between the high-speed (upper) and low-speed (lower) regions. The large integral length scales further enhance the load fluctuations perceived by the rotor but have a negligible effect on the mean wake field quantities and the wake recovery. The lower half region featured a faster breakdown of tip vortex structure and a rapid drop of swirl number, a phenomenon conjectured to be a consequence of the strong turbulence intensities and Reynolds stresses in the lower half region. Furthermore, the sheared turbulent inflow also results in a very intensive energy redistribution process towards large-scale, low-frequency motions, which is important to the downstream turbines.

16 TIDAL AND WAVE POWER↗

Low-Flow Marine Hydrokinetic Turbine for Small Autonomous Unmanned Mobile Recharge Stations

A prototype low-flow marine current turbine for deployment from a small unmanned mobile floating platform has been developed for autonomously seeking and harnessing tidal/coastal currents. The support platform is an unmanned surface vehicle (USV), in the form of a catamaran with two electric outboard motors and with capabilities for autonomous navigation. The USV utilized is a WAM-V 16 vehicle that has been developed separately with support from the Office of Naval Research (ONR) [1]. The marine current turbine is based on a freestream waterwheel (FSWW), also known as an undershot waterwheel (FSWW), mounted on the stern of the USV. The concept of operation involves the USV autonomously navigating to a designated marine current resource. Upon arrival, the USV anchors itself, aligns with the current, and deploys the FSWW turbine using a custom cable-lift mechanism. The turbine harnesses the local current, and an onboard power-take-off (PTO) device converts the mechanical energy into electricity, which is stored in an onboard battery bank. When energy harvesting is completed, the turbine and the anchor are retrieved and the USV navigates to a selected location. These unmanned at-sea platforms can provide power to other unmanned maritime systems. Specifically, in this project, the power generated onboard can be used to charge aerial drones via a custom flight deck that has been developed for the USV. The recharging capabilities offered by a fleet of such strategically placed recharging stations can significantly benefit aerial drones operating in the maritime domain by eliminating the need to travel back and forth to land or ship based charging stations. The project has resulted in the development of subcomponents, including the FSWW turbine, a novel PTO, an automated anchoring system for the USV, an automated turbine deployment system, and a flight deck with capabilities onboard the USV for landing, direct-contact charging and takeoff of aerial drones. The design and development of these subsystems have culminated in the overall prototype marine hydrokinetic platform (MHK Platform, Fig. 1). Comprehensive lab and field testing have been conducted to validate the functionality and performance of the platform and its components. The project demonstrates the potential for autonomous, unmanned systems to harness renewable energy from marine currents, and provide sustainable power solutions for maritime applications such as coastal surveillance and environmental monitoring; shoreline mapping; search and rescue; oceanographic research; inspection and maintenance of offshore energy installations like wind turbines and oil rigs; oil spill response; maritime disaster response; and aerial surveys, as well as facilitation of data transfer drones and shore stations.

16 TIDAL AND WAVE POWER↗

Public Reference Data for Megawatt-Scale Hydrogen Electrolysis - Simulated Wave

The U.S. Department of Energy and the National Laboratory of the Rockies (NLR) demonstrate hydrogen electrolysis, hydrogen compression and storage, and variable hydrogen fuel cell power production using megawatt-scale equipment at NLR’s Flatirons Campus as part of the Advanced Research on Integrated Energy Systems (ARIES) initiative. This dataset represents part of that effort and is intended for academic, national laboratory, industrial, and other stakeholders to plan, design, and validate models of megawatt-scale hydrogen technologies and diverse energy infrastructure nationwide. These data provide a baseline for how existing hydrogen electrolysis technologies perform when coupled with various energy technologies. Future datasets will demonstrate how existing hydrogen fuel cell technologies can provide controllable, dispatchable, and variable power output for artificial intelligence (AI) data centers and other variable loads. This dataset entry describes hydrogen production using a single, simulated wave energy conversion device. The electrolyzer is a 1.25-MW proton exchange membrane type MC250 system manufactured by Nel Hydrogen. While the unit supports up to 2.5 MW of electrolysis, NLR only has a single 1.25-MW electrolysis stack. For the wave energy, NLR used a wave energy converter model from PacWave. These devices can be equipped with accumulators and pressure relief values to smooth the power output by storing and releasing hydraulic energy. Using a peak power output of 10 MW, the model created two 25-minute profiles: one with and one without the accumulators and pressure relief valves. To down select the profile data from the native resolution of 20 Hz to 1 Hz, NLR took the mean of every 20 data points. NLR experimented with two simulated wave energy power plants: one that peaks at 10 MW, and one that peaks at 5 MW. These profiles were scaled for the physical 1.25 MW electrolyzer by multiplying the original profiles by one eighth and one quarter, respectively. The first profile matches the capacity rating of eight of the 1.25 MW electrolyzers, while the second matches four electrolyzers. Finally, NLR experimented with two settings for the electrolyzer power supply minimum and maximum current ramp rates (gain and slew): 200 and 400 amperes per second. The simulated profiles were translated from power (kilowatts) to current (amperes) using a curve fit with calibration data and sent to the electrolyzer power supply at 1-Hz frequency. These datasets report relevant hydrogen balance-of-plant and system data, all captured at 1 Hz, including hydrogen mass production measured with an Emerson Coriolis flow meter. Each .zip file represents a single wave electrolysis experiment and is formatted as follows: {technology}-{accumulator?}_{number of 1.25 MW electrolyzers connected}-{electrolyzer ramp rate in amperes/second} For instance, “wavePacWave-Noacc_4-400.zip” represents the 25 minute-long experiment using the PacWave’s wave energy converter model, equipped with no accumulator, connected to four 1.25-MW electrolyzers with their power supplies set to a maximum current ramp rate (gain and slew) of 400 A/s. Each .zip folder contains the following files: A .csv file containing raw data. An .xlsx file explaining all the fields in the raw data. A .png plot showing the time series of hydrogen production in kilograms per hour, electrolysis power consumption, and input wave power. An experiment, labeled “characterization_200.zip”, demonstrates the MC250 electrolyzer steady-state response with 30 minute load steps for a total duration of 5 hours. Finally, a .csv file is provided with all wave profiles combined into one dataset labeled "combined_wave_experiments.csv". NLR also built an AI/machine-learning predictive model based on these datasets. The model ingests the electrolyzer current command in amperes, as well as various pressures and temperatures across the system, and predicts hydrogen output in kilograms per hour. The complete model can be found at https://huggingface.co/NatLabRockies/ptmelt-hydrogen-electrolysis.

08 HYDROGEN↗

Dynamics of the young binary LMC cluster NGC 1850

BV CCD images and echelle spectra of 52 supergiants are used to examine the age and internal dynamics of the young binary LMC cluster NGC 1850. A color-magnitude diagram was constructed and found to contain three distinct populations of stars. Using star-subtracted, median filtered BV images, attempts were made to determine ellipticity parameters, BV luminosity profiles were constructed to project radii greater than 40. A power law model was applied to test for the presence of a tidal cutoff in the luminosity profile. Of the 52 stars with echelle spectra, a subset of 36 were used to study the cluster dynamics. A rotational signal in the radial velocities has been detected at the 93-percent confidence level, implying a rotation axis at a position angle of 100 +/- 40 deg. Values for the slope of the mass function were determined using mass luminosity relationships and different forms for the IMF. The current cluster age is similar to its central relaxation time.

Fischer, Philippe↗

Marine renewable energy for Arctic observations

Arctic observations are becoming increasingly valuable as researchers investigate climate change and its associated concerns, such as decreasing sea ice and increasing ship traffic. Networks of sensors with frequent sampling capabilities are needed to run forecast models, improve navigation, and inform climate research. Sampling frequency and deployment duration are currently constrained by battery power limitations. In-situ power generation using marine renewable energy sources such as waves and currents can be used to circumvent this constraint. Wave and current resources vary spatially and temporally in the Arctic, with some locations and seasons being better suited for marine renewable energy power generation. Locations and seasons with small resources may still be able to use marine renewable energy because of the low power requirements of the instruments. In this study, we describe the wave and current resources in the Arctic, outline the electricity generation developments that are needed to utilize the resources, and suggest use cases. Wave and current energy converters developed to power observations in the Arctic could also be used to power observations at lower latitudes. Marine renewable energy has the potential to decrease dependence on batteries and improve data collection capabilities in the Arctic; however, this would require the development of new low power technologies that can operate in extreme Arctic environments.

16 TIDAL AND WAVE POWER↗

Survey and Assessment of the Ocean Renewable Energy Resources in the US Gulf of Mexico

This study was conducted by the National Renewable Energy Laboratory (NREL) and funded by the Bureau of Ocean Energy Management (BOEM). It provides a comprehensive feasibility assessment of multiple offshore renewable energy technologies in the Gulf of Mexico (GoM) to inform BOEM's strategic plans related to possible Outer Continental Shelf alternative energy leasing activities in the GoM. In coordination with Gulf Coast states, the study includes some information on offshore renewable energy potential in state waters for future energy planning. The goal of the study is to survey potential offshore renewable energy sources in the GoM and quantify their feasibility relating to resource adequacy, technology maturity, and the potential for competitive cost. The study provides a review of available technologies and concepts for generating offshore renewable energy, including a high-level assessment of the current state of each technology and its potential for future advances. It provides a breakdown of resource capacity for each renewable energy technology and a recommendation that offshore wind be pursued for future study as the most promising technology. The renewable technologies that were considered include offshore wind, wave energy, tidal energy, ocean current energy, offshore solar energy, ocean thermal energy conversion (OTEC), cold water source cooling, and hydrogen (as a storage medium to utilize existing pipeline infrastructure). The resource capacity for each of these renewable energy sources was quantified for both the gross resource capacity potential (gross resource) and the technical resource capacity potential (technical resource) using the methodology described in an earlier NREL report. Many of these sources are very immature from a commercial perspective, which makes some of the comparisons difficult. In many cases, new methods were developed to estimate nominal power density for each technology type, which were necessary to convert the resource areas into deployable gross and technical resource capacity potentials.

17 WIND ENERGY↗

Review of Wave Energy Converter Power Take-Off Systems, Testing Practices, and Evaluation Metrics: Preprint

While the field of wave energy has been the subject of numerical simulation, scale model testing, and precommercial project testing for decades, wave energy technologies remain in the early stages of development and must continuing proving themselves as a promising modern renewable energy field. One of the difficulties that wave energy systems have been struggling to overcome is the design of highly efficient energy conversion systems that can convert the mechanical power, derived from the oscillation of wave activated bodies, into another useful product. Often the power take-off (PTO) is defined as the single unit responsible for converting mechanical power into another usable form such as electricity, pressurized fluid, compressed air, and others. The PTO, and the entire power conversion chain (PCC), is of great importance as it affects not only how efficient wave power is converted into electricity, but also contributes to the mass, size, structural dynamics, and levelized cost of energy (LCOE) of the wave energy converter (WEC). Unlike wind and solar, there is no industrial standard device, or devices, for wave energy conversion and this diversity is transferred to the PTO system. The majority of current WEC PTO systems incorporate a mechanical or hydraulic drive train, power generator, and an electrical control system. The challenge of WEC PTO designs is designing a mechanical-to-electrical component that can efficiently convert irregular, bi-directional, low frequency and low alternating velocity wave motions. While gross average power levels can be predicted in advance, the variable wave elevation input has to be converted into smooth electrical output and hence usually necessitates some type of energy storage system, such as battery storage, accumulator super capacitors, etc., or other means of compensation such as an array of devices. One of the primary challenges for wave energy converter systems is the fluctuating nature of wave resources, which require WEC components to be designed to handle loads (i.e. torques, forces, and powers) that are many times greater than the average load. This approach requires a much greater PTO capacity than the average power output and indicates a higher cost. In addition, supporting mechanical coupling and or gearing can be added to the PCC to help alleviate the difficulties with transmission and control of fluctuating large loads with low frequencies (indicative of wave forcing) into smaller loads at higher frequencies (optimum for conventional electrical machine design) can quickly increase the complexity of the PCC which could result in a greater number of failure modes and increased maintenance costs. All of the previous points demonstrate how the PTO influences WEC dynamics, reliability, performance and cost which are critical design factors. This paper further explores these topics by providing a review of the state-of-the-art PTO systems currently under development, how these novel PTO systems are tested and derisked prior to precommercial deployment, and the evaluation metrics historically used to differentiate between PTO designs and how they can be improved to support control co-design focused development of wave energy systems.

laboratory testing↗

Non-Synchronous Rotation on Europa Driven by Ocean Currents

It has been suggested that the ice shell of Jupiter's moon Europa may drift non-synchronously due to tidal torques. Here we argue that torques applied by the underlying ocean are also important and can result in non-synchronous rotation. The resulting spin rate can be slightly slower than the synchronous angular rate that would have kept the same point of the ice shell facing Jupiter. We develop an ice shell rotation model, driven by ocean stress calculated using a high-resolution state-of-the-art ocean general circulation model, and take into account the viscoelastic deformation of the ice shell. We use the ice shell model results together with observed limits on the ice shell drift speed to constrain ice shell parameters such as effective viscosity, which is currently uncertain by at least four orders of magnitude. Our results suggest, at best, sluggish ice shell convection. Depending on the relaxation time scale of the ice shell and on the ocean currents, the ice shell may exhibit negligible drift, constant drift, or oscillatory drift superimposed on random fluctuations. The expected rotation rate exceeds ~30 m/yr; future spacecraft observations can be used to test these predictions and yield insight into the properties of the ice shell and underlying ocean.

15 GEOTHERMAL ENERGY↗

A Multi-variable, Multi-value Hydrodynamic Modeling Approach to Support Marine Energy and Coastal Resilience Applications

Funded by the Marine Energy Seedling Laboratory Program, the study reported on here aimed to develop a multi-variable, multi-value hydrodynamic modeling approach based on the Finite-Volume Community Ocean Model (FVCOM) to support a wide range of marine renewable energy and coastal resilience applications. We migrated the marine hydrokinetic energy module to simulate tidal energy extraction by tidal turbines under wave-current interactions. We explored the particle tracking module in FVCOM and applied it to Sequim Bay, Washington, to illustrate the surface current field and mimic the pollutant transport near the surface. A tracer-water age module was added to FVCOM to examine water exchange through the entrance. Lastly, a user-specified vertical coordinate option was added to FVCOM to improve simulation of the effect of floating turbines on surface currents and scalar transport. The above-described model development has been tested using a simplified model domain and demonstrated in real-world coastal systems. The outcome of this project will provide a useful modeling code and approach for marine renewable energy and coastal resilience research and applications.

16 TIDAL AND WAVE POWER↗

PacWave Anchoring and Mooring Study

PacWave, with its location in some of the most energetic waters in the nation and a buildout to support grid-connected devices, is poised to become a leader in field testing of wave energy converters (WECs) at high technology readiness levels. As part of the device deployment and testing protocols at PacWave, the client is responsible for providing all mooring system components, since there are currently no mooring system components specified for PacWave. NREL and PNNL have been tasked with conducting a preliminary analysis of permanent or temporary mooring systems at the PacWave South site. Previous work for this task included a global trade study of mooring systems used for WECs, and a site characterization of PacWave South. This current report will use the results of the previous studies to inform the design of various mooring systems to be installed at PacWave, which will allow cost analyses to be performed to compare the costs of acquisition of these mooring systems and the costs of mooring systems designed specifically for clients' devices.

16 TIDAL AND WAVE POWER↗

High- and Mid-Fidelity Modeling Comparison for a Floating Marine Turbine System: Preprint

There is a lack of suitable numerical tools, particularly open-source tools, that can be used for designing and optimizing marine turbine systems. The National Renewable Energy Laboratory (NREL) has added features to their widely used mid-fidelity wind turbine modeling code, OpenFAST, to enable modeling of axial flow marine turbines. This necessitated the addition of several physical effects relevant to marine turbines that can be neglected for wind turbines. These include buoyant loads, added mass and inertia loads, wave-current superposition, and changes to the coordinate systems. This updated version of OpenFAST allows for the modeling of both fixed and floating marine turbine systems at a speed comparable to real time. While efficient for long simulations, large sets of load cases, and design studies, mid-fidelity codes cannot capture all of the potentially important physical phenomenon impacting marine turbine systems. High-fidelity computational fluid dynamics (CFD) simulations can capture more flow effects with fewer assumptions and provide detailed body pressure mapping and flow-field information. It is important to compare predictions between mid-fidelity and high-fidelity codes, both to verify the models and to understand the limitations. A floating marine turbine system designed by NREL was modeled both with OpenFAST and with the commercial CFD code, STARCCM+. The CFD model used a 3-D unsteady Reynolds-averaged Navier-Stokes solver for a volume-of-fluid numerical wave and current tank. The blade-resolved simulations used the sliding-interface technique for the spinning rotor and an overset grid to accommodate the rigid-body motion of the floating system. The mooring system was modelled with a custom coupling of the CFD solver with the open-source code, MoorDyn. This improves upon the existing quasi-static catenary solver in STARCCM+, which lacks seabed contact or line-to-line connections. Spatial and temporal convergence studies were conducted. The simulation results for a combined current and wave condition are compared between OpenFAST and CFD, highlighting the capabilities of the mid-fidelity code and identifying the areas where a high-fidelity approach is needed.

CFD↗

Evaluation of a Wave Powered Water Pump Performance by Ocean Field Testing and WEC-Sim Modeling

This submission from AMEC (the Atlantic Marine Energy Center) includes data from an ocean field deployment of a wave powered water pump in March 2023. The wave pump is an upweller device, designed to enhance macroalgal aquaculture. The wave pump device was deployed off the coast of Isles of Shoals Appledore Island in Maine, USA. The data were collected using a custom-built DAQ module comprised of Arduino Unos. GPS time stamp accompanies the data. The data are volumetric flow rate from the wave pump, and relative motion of the device between float and spar buoys. Flow rate is measured by flow meter, and relative motion is measured by lidar. Calibration data for the lidar and flow meter sensors are included. This data set also includes synchronous Sofar Spotter buoy data from a mooring approximately 300 feet away from the wave pump mooring. Video data from the deployment are included from both on-board the device sporadically throughout the deployment, and from a webcam for a short duration of the deployment. Hydrophone data were also taken co-currently, and are available by contacting Martin Wosnik at the University of New Hampshire. The Matlab code used to process the field data is incorporated. A biological assessment is included which aided the NEPA consultation process, prior to conducting the field deployment. A WEC-Sim numerical model of the wave pump, and a re-design effort are part of this work. Code used to validate the WEC-Sim model from the field data are also included.

16 TIDAL AND WAVE POWER↗

Lessons learned from the design and operation of a small-scale cross-flow tidal turbine

In 2023, a first-generation prototype of a small-scale marine current turbine was operated in Sequim Bay, Washington (USA) for 141 days. The system, referred to as the Turbine Lander, was the product of a laboratory-to-field effort to develop a system that enables enhanced ocean sensing or vehicle recharge in remote, energetic settings. The turbine consists of a vertical-axis, cantilevered rotor (1.19 m x 0.85 m) with four foils installed on a gravity foundation. A broader range of constraints including the deployment strategy, site characteristics, and estimated loads, drove the system’s design. This work presents the design, characterization, operation, and post-recovery engineering assessment of the Turbine Lander. Pre-deployment characterization efforts yielded a peak power coefficient of approximately 0.3 for the rotor, although system losses resulted in much lower water-to-wire efficiencies under most operating conditions. The results demonstrate the importance of co-design among key components of the powertrain and control systems to achieve acceptable system efficiency across operating conditions.

Co-design↗

A Comparison of Battery Charge Controller Technologies for Wave Energy Converters

Wave energy is a uniquely challenging field for electrical system designers. High peak and low average power potential with a constantly varying energy input is difficult to harness and control through conventional means. To power the blue economy, low-powered wave energy converters (WECs) need batteries for energy storage. Safely and effectively charging batteries from waves requires a charge controller to properly monitor and control voltage and current going to the battery. Currently, off-the-shelf charge controllers exist for other renewable generation such as wind, hydro, and solar. Two topologies were validated: a buck converter and a pulse width modulation (PWM) charge controller. Using an in-lab dry testbed, wave energy power inputs were simulated to properly validate the effectiveness of existing charge controller technologies, identifying the shortcomings and improvements needed to effectively harness wave energy.

battery storage↗

A Comparison of Battery Charge Controller Technologies for Wave Energy Converters: Preprint

Wave energy is a uniquely challenging field for electrical system designers. High peak and low average power potential with a constantly varying energy input is difficult to harness and control through conventional means. To power the blue economy, low-powered wave energy converters (WECs) need batteries for energy storage. Safely and effectively charging batteries from waves requires a charge controller to properly monitor and control voltage and current going to the battery. Currently, off-the-shelf charge controllers exist for other renewable generation such as wind, hydro, and solar. Two topologies were validated: a buck converter and a pulse width modulation (PWM) charge controller. Using an in-lab dry testbed, wave energy power inputs were simulated to properly validate the effectiveness of existing charge controller technologies, identifying the shortcomings and improvements needed to effectively harness wave energy.

battery storage↗

Enabling the Electrification of Offshore Activities – Co-Demonstration of Next-Generation Autonomous Offshore Power System and Resident, Uncrewed Mobile and Static Assets at PacWave Wave Energy Test Site

Oceans cover two-thirds of the earth's surface and form the world's biggest and best – yet largely untapped – battery. Ocean waves have more energy density than other renewables, including wind, solar, and biomass, and have the potential to supply 4x the world's annual energy consumption (Masterson, 2022; Zic, 2020). In addition to the impact wave energy can have on decarbonizing and diversifying the electric grid, it offers a significant value proposition in the emerging blue economy sector (LiVecchi et al, 2019). The blue economy consists of industries operating offshore, including shipping, oil and gas, defense and security, aquaculture, and research. These industries require bringing people and energy on site to perform daily work, but current energy costs in the blue economy are extremely high. Here, the prevailing processes are complex, including shore dependencies and fuel transportation logistics. Few alternatives for reliable power generation exist, with the most prominent being high cost and high carbon emissions diesel generation. Because of this lack of affordable, reliable power, the trends of electrification, digitization, and automation that have led to substantial innovation and improvements in the terrestrial economy over the last two decades are slow to come to the blue economy.

16 TIDAL AND WAVE POWER↗