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At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Design, Optimization, and Control of Floating Offshore Wind Farms for Optimal Energy Production (Final report)

The uncertainty and irregularity of ocean waves and the ocean environment is a major factor in the development of commercial scale floating wind turbines as the operation of floating structures in such an environment can lead to irregular and unpredictable loading, fatigue, and ultimately a reduction in the operational life of the turbine system which affects energy production over the lifetime of the turbine. Control solutions that can limit float motions and mitigate stressful events on the structure become essential for extending lifetime and limiting the operational uncertainty of a floating wind turbine. Digital twins are computational replicas of physical systems that operate in parallel with the operation of the physical system. Given advanced knowledge of a systems input, digital twins have the ability to predict the behavior of a system in advance, which can be valuable in the control of that system. In this project, we developed and assessed potential digital twin models developed in house and openly available (OpenFast) for use in the real time control of the six degree of freedom response motions of a floating wind turbine in ocean waves. Coupling these models with near-field real time irregular sea surface (wve) measurement/sensings and prediction models, we used the digital twin to predict how the floating turbine will respond to the incoming waves. Applying this information to a motion control system of the float, one can limit and control float motions to prevent undesirable loading events/large angular motions, thus increasing system life and ultimately contributing to optimizing energy production. Due to the computational intensity of operating a digital twin in real time, we investigated the use of artificial intelligence techniques to speed-up the processes of the digital twin, as well as the wave reconstruction/prediction models. Model tank testing at the University of Rhode Island and University of Maine both validated and demonstrated the developed techniques on simple float geometries and a scale model of the NREL 15 MW reference turbine.

17 WIND ENERGY↗
DOE OSTI2020

Mapping of Benthic Habitats at Marine Renewable Energy Sites Using Multibeam Echosounder and Sediment Profile Imaging Technologies

Objectives/Scope: The goal of this work was to develop a consistent and semi-automated seafloor survey method for generating high-resolution, benthic habitat maps for environmental assessments and monitoring of marine renewable energy sites. Sediment profile and plan view imaging (SPI/PV) technology was combined with multibeam bathymetry and acoustic backscatter methods to demonstrate a rapid, cost-effective benthic mapping protocol. A key technical innovation of this project was the development of an image processing platform that automatically measures key features from the images. Methods: Multibeam echosounder (MBES) acoustic and SPI/PV surveys were conducted at three coastal areas off the U.S. west coast, including the PacWave South energy test site off of Newport, Oregon. Point data on physical and biological sediment conditions obtained from the SPI/PV imagery were used to efficiently ground-truth the high-resolution MBES bathymetry and backscatter mosaics. The SPI camera is an optical corer that obtains an undisturbed 21 by 15 cm, high-resolution, cross-sectional image of the sediment–water interface and upper sediment column. The plan view camera attached to the SPI camera frame captures a downward looking view of the seabed immediately before the SPI image is obtained. As part of this project, we developed a computer vision image processing platform (iSPI) that uses deep convolutional neural networks and other approaches to automatically identify and measure key features in the images, such as grain size and surface relief. Results: Detailed benthic habitat maps were generated using this mapping approach for three different marine settings. The sites mapped included a silt-dominated embayment; a sloping, nearshore, transitional very fine to coarse sand bottom; and a medium, sand-dominated continental shelf marine energy test site. In each case, acoustic and imaging surveys were completed in less than week, and detailed benthic habitat maps were generated within 60 days. The results were placed within the Coastal and Marine Ecological Classification Standard (CMECS) habitat mapping framework, and various combinations of the bathymetry, backscatter, and SPI and PV data were used to generate CMECS component maps. Novel Information: This project developed and demonstrated a repeatable and cost-effective approach for efficiently mapping benthic habitat conditions over broad areas of the seafloor by combining state-of-the-art acoustic and imaging techniques. The primary survey tools used in this project have been used previously in both the offshore renewable (wind) and oil and gas sectors to map and monitor benthic environments. This project’s innovations include 1) the focused use of high-resolution SPI/PV imagery to ground-truth acoustic mosaics, and 2) the development of a computer automated image analysis processing tool that both streamlines and standardizes the generation of data from the imagery and makes the data extraction process more cost-effective and repeatable.

13 HYDRO ENERGY↗
DOE OSTI2024

Monitoring of Photovoltaic (PV) Performance and Degradation: Integrated Renewable Energy Systems (IRES) - PV Monitoring Task

The Integrated Renewable Energy System (IRES) testbed demonstration at the Pacific Northwest National Laboratory (PNNL) Sequim campus includes development of a suite of capabilities for tracking the performance of photovoltaic (PV) renewable energy components located on a floating platform (floating PV) and on a shoreline building rooftop. The marine environment represents potentially harsh and corrosive conditions for PV modules. Compared to terrestrial PV, potential concerns for offshore PV arising from high humidity and occasional contact with saltwater, marine wildlife, and aquaculture. These environmental factors can reduce electricity generation efficiency and increase the risk of electrical faults, polymer insulation or jacketing degradation and hydrolysis of the PV cell encapsulant materials. Offshore PV modules may also be exposed to lower temperatures and buoyant and vibrating motions with a floating platform. It is not clear how the long-term performance of floating PV will be affected by these factors. To understand expected energy generation through solar cells on a floating platform, monitoring of the performance of PV modules in the marine environment is needed. This report outlines a plan for long-term testing of IRES PV components utilizing resources of the PNNL Material Aging and Detection (MAaD) Science team and the Marine and Coastal Research Laboratory (MCRL). Equipment applicable for onsite testing and real-time monitoring of the PV performance associated with environmental conditions including temperature, solar irradiance, shading and soiling is included. In case of performance loss, equipment for fault detection, failure analysis, material testing, and further troubleshooting are also available. Through establishment of this capabilities, the enabling IRES project sets the stage for future research to advance off-shore and near-shore energy options for businesses and communities.

14 SOLAR ENERGY↗
DOE OSTI2022

Geographic patterns and determinants of antibiotic resistomes in coastal sediments across complex ecological gradients

Coastal areas are highly influenced by terrestrial runoffs and anthropogenic disturbances, commonly leading to ecological gradients from bay, nearshore, to offshore areas. Although the occurrence and distribution of sediment antibiotic resistome are explored in various coastal environments, little information is available regarding geographic patterns and determinants of coastal sediment antibiotic resistomes across ecological gradients at the regional scale. Here, using high-throughput quantitative PCR, we investigated the geographic patterns of 285 antibiotic resistance genes (ARGs) in coastal sediments across a ~ 200 km scale in the East China Sea. Sediment bacterial communities and physicochemical properties were characterized to identify the determinants of sediments antibiotic resistome. Higher richness and abundance of ARGs were detected in the bay samples compared with those in nearshore and offshore samples, and significant negative correlations between the richness and/or abundance of ARGs and the distance to coastline (DTC) were identified, whereas different types of ARGs showed inconsistency in their relationships with DTC. The composition of antibiotic resistome showed significant correlations with nutrition-related variables (including NH 4 + -N, NO 3 − -N, and total phosphorus) and metals/metalloid (including As, Cu, Ni, and Zn), suggesting that terrestrial disturbances largely shape the antibiotic resistome. The Bipartite network showed strong associations between ARGs and mobile genetic elements (MGEs), and Partial Least Squares Path Modeling further revealed that terrestrial disturbance strength (as indicated by DTC) directly affected abiotic environmental conditions and bacterial community composition, and indirectly affected antibiotic resistome via MGEs. These findings provide insights into regional variability of sediment antibiotic resistome and its shaping path across complex ecological gradients, highlighting terrestrial disturbances as determinative forces in shaping coastal sediment antibiotic resistomes.

Xiong, Shangling↗
DOE OSTI2021

Efficient marine environmental characterisation to support monitoring of geological CO 2 storage

Carbon capture and storage is key for mitigating greenhouse gas emissions, and offshore geological formations provide vast CO 2 storage potential. Monitoring of sub-seabed CO 2 storage sites requires that anomalies signifying a loss of containment be detected, and if attributed to storage, quantified and their impact assessed. However, monitoring at or above the seabed is only useful if one can reliably differentiate abnormal signals from natural variability. Baseline acquisition is the default option for describing the natural state, however we argue that a comprehensive baseline assessment is likely expensive and time-bound, given the multi-decadal nature of CCS operations and the dynamic heterogeneity of the marine environment. We present an outline of the elements comprising an efficient marine environmental baseline to support offshore monitoring. We demonstrate that many of these elements can be derived from pre-existing and ongoing sources, not necessarily related to CCS project development. We argue that a sufficient baseline can be achieved by identifying key emergent properties of the system rather than assembling an extensive description of the physical, chemical and biological states. Further, that contemporary comparisons between impacted and non-impacted sites are likely to be as valuable as before and after comparisons. Furthermore, as these emergent properties may be nuanced between sites and seasons and comparative studies need to be validated by the careful choice of reference site, a site-specific understanding of the scales of heterogeneity will be an invaluable component of a baseline.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Limited increases in Arctic offshore oil and gas production with climate change and the implications for energy markets

Climate change impacts on sea ice thickness is opening access to offshore Arctic resources. The degree to which these resources are exploited will depend on sea-ice conditions, technology costs, international energy markets, and the regulatory environment. We use an integrated human-Earth system model, GCAM, to explore the effects of spatial–temporal patterns of sea-ice loss under climate change on future Arctic offshore oil and gas extraction, considering interactions with global energy markets and emission reduction scenarios. We find that under SSP5, a “fossil-fueled development” scenario, the effects of sea-ice loss are larger for Arctic offshore oil production than gas. Under SSP5, future extraction of Arctic offshore oil and gas through 2100 adds roughly 0.8–2.6 EJ/year to oil and gas markets but does not have large impacts on global oil and gas markets. Surprisingly, a low-carbon scenario results in greater Arctic offshore oil production to offset the more emissions-intensive unconventional oil production.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

The revised FLORIDyn model: implementation of heterogeneous flow and the Gaussian wake

In this paper, a new version of the FLOw Redirection and Induction Dynamics (FLORIDyn) model is presented. The new model uses the three-dimensional parametric Gaussian FLORIS model and can provide dynamic wind farm simulations at a low computational cost under heterogeneous and changing wind conditions. Both FLORIS and FLORIDyn are parametric models which can be used to simulate wind farms, evaluate controller performance and can serve as a control-oriented model. One central element in which they differ is in their representation of flow dynamics: FLORIS neglects these and provides a computationally very cheap approximation of the mean wind farm flow. FLORIDyn defines a framework which utilizes this low computational cost of FLORIS to simulate basic wake dynamics. This is achieved by creating so-called observation points (OPs) at each time step at the rotor plane which inherit the turbine state. In this work, we develop the initial FLORIDyn framework further considering multiple aspects. The underlying FLORIS wake model is replaced by a Gaussian wake model. The distribution and characteristics of the OPs are adapted to account for the new parametric model but also to take complex flow conditions into account. To achieve this, a mathematical approach is developed to combine the parametric model and the changing, heterogeneous world conditions and link them with each OP. We also present a computationally lightweight wind field model to allow for a simulation environment in which heterogeneous flow conditions are possible. FLORIDyn is compared to Simulator for Offshore Wind Farm Applications (SOWFA) simulations in three- and nine-turbine cases under static and changing environmental conditions. The results show a good agreement with the timing of the impact of upstream state changes on downstream turbines. They also show a good agreement in terms of how wakes are displaced by wind direction changes and when the resulting velocity deficit is experienced by downstream turbines. A good fit of the mean generated power is ensured by the underlying FLORIS model. In the three-turbine case, FLORIDyn simulates 4 s simulation time in 24.49 ms computational time. The resulting new FLORIDyn model proves to be a computationally attractive and capable tool for model-based dynamic wind farm control.

17 WIND ENERGY↗
DOE OSTI2025

Modeling Offshore Wind Farm Performance in Coastal Low-Level Jets Using Coupled Mesoscale-Microscale Large Eddy Simulations

Accurately predicting wind farm reliability under complex offshore atmospheric conditions remains a key challenge, particularly during noncanonical meteorological events such as coastal low-level jets (LLJs). LLJs, characterized by strong nonmonotonic vertical shear and directional veer, depart significantly from the simplified inflow assumptions embedded in conventional design standards, low-fidelity engineering models, and microscale large eddy simulations of the atmospheric boundary layer. In this work, we use the virtual wind farm framework—an exascale, graphics processing unit–accelerated large eddy simulation platform coupled with high-fidelity aeroservoelastic turbine models and advanced mesoscale-microscale coupling via the ExaWind software stack—to investigate turbine responses under realistic LLJ forcing. Simulations are performed over the U.S. North Atlantic offshore domain with the use of meteorological inputs from New York State Energy Research and Development Authority buoy data, focusing on a representative LLJ case impacting the International Energy Agency 15 MW reference turbine. Our results show that LLJs can cause up to 50% power deficits in downstream turbine rows and significantly amplify low-speed shaft and tower loads through nonlinear coupling between complex inflow characteristics and turbine structural dynamics. Two primary mechanisms drive these load amplifications: (1) unique LLJ inflow features—including veer and vertical/lateral shear—and (2) the downstream evolution of the flow under stable thermal stratification, which suppresses turbulence mixing and alters wake recovery. These mechanisms produce streamwise variations in turbine loading not captured by standard hub height–based metrics or existing design load case (DLC) definitions. This study highlights the critical role of rotor-scale flow gradients in driving fatigue and system-level aeroelastic responses, challenging current DLC and control strategies. We advocate the integration of full-flow field, environment-aware wind inputs into load modeling and control algorithms. By leveraging exascale computing to resolve mesoscale-microscale coupling, this work lays the groundwork for next-generation offshore wind turbine design and operation in meteorologically complex marine environments.

17 WIND ENERGY↗
DOE OSTI2022

Autonomous Aerial Power Plant Inspection in GPS-denied Environments

Inspection of coal-fired power plants is frequently dangerous, includes difficult places to reach, and can turn expensive due to the downtimes and cost of inspection crew. Robotic systems have shown capabilities to address some of these issues, but most of the current robotic inspection technology in power plants is designed for specific components. Conversely, recent advances in machine vision have empowered aerial platforms for long-range, remotely-controlled, GPS-based inspections of industrial plants. This capability has led to wide spread utilization of aerial robots (commonly termed Drones, UVS or UAS) platforms for inspection in less challenging environments where both collision avoidance, and GPS reception are not significant issues. The challenge in adapting airborne technology for power plant inspection lies in internal structures and the complex network of piping, and distribution systems, which impose significant risks for collision and can hinder the reception and transmission of GPS signals. The current state of the art in aerial inspection technology within the energy sector is controlled via radio control, and utilizes GPS-based navigation, for inspection of large-scale plants such as offshore platforms and wind turbine parks. Nevertheless, close-range and autonomous inspection in the GPS-denied environments of power plants has not yet been achieved, as it requires precise guidance and navigation with real-time situational awareness and obstacle avoidance capabilities. This endeavor introduced the use of rotary wing flying robots, due to their station keeping and vertical take-off capabilities for power plant components inspection. To enable close quarter inspection two methods were used. One method uses the 3D CAD (Three-dimensional Computer-Aided Design) model of the asset to inspect to generate the UAV’s inspection path. To acquire, analyze and process the 3D model, first, the STL file is produced to obtain surface points and vectors normal to the surface. Later, by introducing other variables such as wall offset and a controlled trajectory between each outline and each subsequent layer, the flight path is generated. The proposed framework will generate a path that will pass as close as desired from the surface and navigate in intricate environments. A second method, use advanced manufacturing techniques such as CNC (Computer Numerical Control) and additive manufacturing. Once the inspection flight path is obtained, vision-based navigation systems are employed to have the UAV autonomously tracking the provided trajectory. Finally, Artificial Intelligence-enabled developments are in charge of detecting cracks and corrosion in structural components of power plants. The proposed methods are validated in simulations, laboratory and industrial setups, where it is shown that the developed systems acting together enable close-quarter autonomous aerial inspection and mapping in power plant assets. The system can be further improved by adding more sensors to navigate in different GPS-denied environments, with non-homogeneous lighting conditions, dust and in general situations where vision-based systems may fail.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2023

Sensitivity analysis of numerical modeling input parameters on floating offshore wind turbine loads

Abstract. Floating wind turbines must withstand a unique and challenging set of loads from the wind and ocean environment. To de-risk development, accurate predictions of these loads are necessary. Uncertainty in modeling predictions leads to larger required safety factors, increasing project costs and the levelized cost of energy. Complex aero-hydro-elastic modeling tools use many input parameters to represent the wind, waves, current, aerodynamic loads, hydrodynamic loads, and structural properties. It is helpful to understand which of these parameters ultimately drives a design. In this work, an ultimate and fatigue-proxy load sensitivity analysis was performed with 35 different input parameters, using an elementary effects approach to identify the most influential parameters for a case study involving the National Renewable Energy Laboratory (NREL) 5 MW baseline wind turbine atop the OC4-DeepCwind semisubmersible during normal operation. The importance of each parameter was evaluated using 14 response quantities of interest across three operational wind speed conditions. The study concludes that turbulent wind velocity standard deviation is the parameter with the strongest sensitivity; this value is important not just for turbine loads, but also for the global system response. The system center of mass in the wind direction is found to have the highest impact on the system rotation and tower loads. The current velocity is found to be the most dominating parameter for the system global motion and consequently the mooring loads. All tested wind turbulence parameters in addition to the standard deviation are also found to be influential. Wave characteristics are influential for some fatigue-proxy loading but do not significantly impact the extreme ultimate loads in these operational load cases. The required number of random seeds for stochastic environmental conditions is considered to ensure that the sensitivities are due to the input parameters and not due to the seed. The required number of analysis points in the parameter space is identified so that the conclusions represent a global sensitivity. The results are specific to the platform, turbine, and choice of parameter ranges, but the demonstrated approach can be applied widely to guide focus in parameter uncertainty.

17 WIND ENERGY↗
DOE OSTI2022

Advanced Collision Detection and Site Monitoring for Avian and Bat Species for Offshore Wind Energy (Final Technical Report)

This final technical report summarizes the outcomes from a project that aimed to design, build, and test a persistent and autonomous monitoring system for avian and bat collisions with offshore wind turbines blades and structures. The system comprises four primary sensor modules: 1) on-blade sensor modules for collision detection and dual-vision image capture on each blade with both visible light and near-infrared imagers; 2) additional on-blade collision sensors mounted further from the root; 3) a nacelle-mounted unit including a 360º camera and ultrasonic microphone array; and, 4) an on-blade, high-performance infrared camera module. Primary targeted outcomes were high sensitivity for the detection of blade strikes from bats and small birds, and automatically captured visual confirmation of the striking object; these features are critical for monitoring offshore wind turbine installations, where ground-based methods are not viable. In addition, local recording will provide a long-term sensor recording database. Following laboratory validation, field testing was conducted on an operational wind turbine in collaboration with the National Wind Technology Center at the NREL Flatirons campus over two planned field tests.

17 WIND ENERGY↗
DOE OSTI2025

A Review of Offshore Methane Quantification Methodologies

Since pre-industrial times, anthropogenic methane emissions have increased and are partly responsible for a changing global climate. Natural gas and oil extraction activities are one significant source of anthropogenic methane. While methods have been developed and refined to quantify onshore methane emissions, the ability of methods to directly quantify emissions from offshore production facilities remains largely unknown. Here, we review recent studies that have directly measured emissions from offshore production facilities and critically evaluate the suitability of these measurement strategies for emission quantification in a marine environment. The average methane emissions from production platforms measured using downwind dispersion methods were 32 kg h−1 from 188 platforms; 118 kg h−1 from 104 platforms using mass balance methods; 284 kg h−1 from 151 platforms using aircraft remote sensing; and 19,088 kg h−1 from 10 platforms using satellite remote sensing. Upon review of the methods, we suggest the unusually large emissions, or zero emissions observed could be caused by the effects of a decoupling of the marine boundary layer (MBL). Decoupling can happen when the MBL becomes too deep or when there is cloud cover and results in a stratified MBL with air layers of different depths moving at different speeds. Decoupling could cause: some aircraft remote sensing observations to be biased high (lower wind speed at the height of the plume); the mass balance measurements to be biased high (narrow plume being extrapolated too far vertically) or low (transects miss the plume); and the downwind dispersion measurements much lower than the other methods or zero (plume lofting in a decoupled section of the boundary layer). To date, there has been little research on the marine boundary layer, and guidance on when decoupling happens is not currently available. We suggest an offshore controlled release program could provide a better understanding of these results by explaining how and when stratification happens in the MBL and how this affects quantification methodologies.

Riddick, Stuart N. (ORCID:0000000316841843)↗
DOE OSTI2022

Optimization of a Lightweight Floating Offshore Wind Turbine with Water Ballast Motion Mitigation Technology

Floating offshore wind turbines are a promising technology for addressing energy needs by utilizing wind resources offshore. The current state of the art is based on heavy, expensive platforms to survive the ocean environment. Typical design techniques do not involve optimization because of the computationally expensive time domain solvers used to model motions and loads in the ocean environment. However, this design uses an efficient frequency domain solver with a genetic algorithm to rapidly optimize the design of a novel floating wind turbine concept. The concept utilizes a liquid ballast mass to mitigate motions on a lightweight post-tensioned concrete platform. The simple cruciform-shaped design of the platform made of post-tensioned concrete is less expensive than steel, reducing the raw material and manufacturing cost. The use of ballast water to behave as a tuned mass damper allows a smaller platform to achieve the same motions as a much larger platform, thus reducing the mass and cost. The optimization techniques applied with these design innovations resulted in a design with a levelized cost of energy of USD 0.0753/kWh, roughly half the cost of the current state of the art.

Ramsay, William↗
DOE OSTI2023

The Diurnal Cycle of East Pacific Convection, Moisture, and CYGNSS Wind Speed and Fluxes

The far eastern tropical Pacific is one of the rainiest locations on Earth. This region is characterized by a robust diurnal cycle with precipitation initiating over the Andes mountains in Colombia in the late afternoon and moving offshore overnight while organizing into mesoscale convective systems (MCSs). As the MCSs move westward, they can seed tropical easterly waves that develop into tropical cyclones. Novel measurements of near-surface wind speeds and latent heat flux (LHFLX) from the Cyclone Global Navigation Satellite System (CYGNSS) mission and ERA5 reanalysis are used to evaluate changes to regional flow patterns, moisture, and LHFLX that favor a strong westward propagating diurnal cycle of precipitation in this region. Days with strongly versus weakly westward propagating diurnal precipitation are compared during the extended boreal summer of the CYGNSS era (May–October 2018–2021). Strongly propagating days have a more moist lower troposphere with stronger vertically integrated moisture flux convergence than days with weakly propagating precipitation. The enhanced low-level moisture is supported by increased wind-driven LHFLX from stronger regional flows including the Choco and Caribbean Low-Level Jets and Panama and Papagayo gap winds. Increased offshore convergence and vorticity also help sustain convection during the days with strongly propagating precipitation. Background variations in the physical environment, as opposed to diurnal variations, seem more important for supporting a robust diurnal cycle of precipitation in the region.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Exploring Novel Configuration Designs Alternatives for Lazy Wave Submarine Power Cables

Floating offshore wind turbines require a complex integrated design to balance the platform response and station-keeping requirements in a highly dynamic environment. Dynamic subsea power cables are one of the critical components that have to be considered in detail to ensure both extreme, as well as repeated operational conditions do not exceed the cable design limits. This paper presents the design feasibility limits of a 66kV dynamic cable for a lazy wave configuration. The work explores an innovative staggered cable configuration that has the potential to provide additional compliance in shallow water conditions. Both configurations are evaluated using the motions of a representative floating wind platform under development for deployment in relatively shallow water depth of 150m. The assessment was conducted using the hydrodynamic software Orcaflex, incorporating a range of design inputs and design variations. Key parameters analysed include cable curvature and effective tension and bending stress. The alternative cable configuration provides a more gradual crossing of the water column, which would allow to support increased platform excursions in shallow water depths. The design uses a combined buoyancy and bend protection element, offering designers additional options for challenging operational conditions. The paper will be of interest to designers and developers of floating wind projects, providing a comparative assessment between the conventional lazy wave configuration and an innovative alternative that enables larger cable and mooring excursion envelopes in challenging conditions.

16 TIDAL AND WAVE POWER↗
DOE OSTI2024

Challenges and Opportunities for Floating Offshore Wind Energy in Ultradeep Waters of the Central Atlantic

This study, funded under an interagency agreement between the U.S. Department of Energy's (DOE) National Renewable Energy Laboratory (NREL) and Bureau of Ocean Energy Management (BOEM), is intended to provide BOEM with key information to inform their decision making about current and future leasing in the Central Atlantic region of the United States. The report will also benefit state governments, developers, research institutions, and the public which are seeking technical and market-based information about the unique aspects of the offshore wind energy development along the outer continental shelf of the Central Atlantic region of the United States. The study provides a broad top-level assessment of the key challenges and opportunities that are unique to offshore wind energy development in the Central Atlantic region. It focuses on BOEM's Central-Atlantic region Call areas. The research is based on the most current technology, deployment, and stakeholder information available to NREL. The topics include assessments of the physical environment, current leasing status and major stakeholder issues, state and federal energy policy, an assessment of future leasing requirements based on state targets, status and limitations of the technology, and supply chain status. The primary intent is to inform the readers about the prospects for deploying offshore wind in the designated deep water Call areas, E and F, identified by BOEM. The report makes recommendations regarding development in these regions.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Toward prediction of turbulent atmospheric flows over propagating oceanic waves via machine-learning augmented large-eddy simulation

Wind-wave interactions have important effects on the energy harvesting of offshore wind farms. High-fidelity large-eddy simulation (LES) is a powerful approach for investigating wind-wave interactions in turbulent oceanic environments. Due to the large scale of the flow domain and the high grid resolution required to resolve multi-scale flow motions, however, brute-force LES of wind-wave interactions is computationally very expensive. We propose augmenting brute-force LES via machine-learning data-driven modeling (ML-LES) to dramatically reduce the computational time required to obtain converged turbulence statistics when the brute-force approach is employed. Namely, we employ a convolutional neural network (CNN) autoencoder trained and validated with LES data sets to develop a highly efficient ML-LES approach for computing turbulence statistics from just a few snapshots of instantaneous LES flow fields. Further, our results demonstrate the accuracy and efficiency of ML-LES in predicting the mean velocity, velocity fluctuations, and turbulence kinetic energy in highly stretched computational grid systems required to carry out simulations in real-life oceanic environments.

42 ENGINEERING↗