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At least 19 records

Metocean Reference Station Best Practices: MORS-1 Case Study

The goal of a Metocean Reference Station should be to aid both near-term development of the offshore wind energy industry as well as long-term climate and energy research. Capitalizing on existing shared-use facilities wherever possible, reference stations should provide data valued by industry users as well as research users in a cost-effective way. Cost-effectiveness is a critical component of developing a reference site, as the real value of the site's data collection efforts is the length of the time series it is able to sustain. This report seeks to lay out the best practices toward developing and maintaining metocean reference stations in the United States. The best practices described here focus on suitable platforms, sensor integration, and long-term operations of the reference station itself, as best practices of operations for individual sensors for the research community or validation enterprises focused on industrial use of metocean data are well described in the literature. This work focuses on potential stations in the United States because the market for reference data and validation facilities is less well defined in the United States, given the young age of the rapidly emerging offshore wind energy industry here.

17 WIND ENERGY↗

Development of a Metocean Reference Site near the Massachusetts and Rhode Island Wind Energy Areas

This project developed the first long-term U.S.-based offshore MetOcean Reference Site (MORS-1) by capitalizing on a unique combination of one of the few existing publicly available offshore wind energy metocean observational campaigns in the United States and the only existing research-grade offshore fixed tower. Data collected at MORS-1 has facilitated improved wind resource assessments, improved short-term power production estimates, and reduced costs for sensor validation and calibration efforts, which translate into reduced overall wind energy project risk and cost for developers. Now operational, MORS-1 serves the needs of both industry and researchers using a nonprofit, joint industry-academic partnership model. Led by the Woods Hole Oceanographic Institution, the MORS-1 development effort focused on creating both a recognized organizational structure that will ensure support of the MORS-1 by the wider wind energy industry and research community, and a highly validated data collection and sensor validation facility that will serve as the premier location for cost- and uncertainty-reducing resource characterization and research efforts.

17 WIND ENERGY↗

Infrastructure and Metocean Technology

<strong>Research Problem: </strong>Changes in the ocean environment (i.e., mudslides or burial from subsea currents, strong weather events or natural fluctuations) have been linked to <strong>billions of dollars of impacts</strong>. These events can have a significant effect on the <strong>success and longevity </strong>of offshore infrastructure, as well as affect <strong>safety and cost </strong>during exploration and production activities.<strong>Research Approach: (1) </strong>Determine current state of knowledge regarding hazardous metocean and bathymetric conditions, and data availability regarding these conditions and historic events. (2) EY19 -Evaluate if Ml/AI model can be developed to better identify current hazardous metocean and bathymetric conditions. (3) EY 20 + -develop, train, and test ML/AI model to identify current conditions and forecast changes and vulnerability that may impact offshore infrastructure and operations. <strong>Benefit: </strong>Improved characterization of seabed related hazards in the offshore environment will help to manage and minimize costs and risks during drilling and production operations, and help prevent catastrophic incidents.

Duran, Rodrigo↗

Reducing Uncertainty in Offshore Wind Energy Yield Estimates via a Metocean Reference Site

The offshore wind industry is burgeoning in the coastal waters of the United States, specifically along the Atlantic. For wind energy to be successful, reliable observations and model simulations are needed for resource assessment and forecasting. While many of these activities have already begun, there is currently an absence of observations at hub-height in these waters, with the closest available hub-height measurements usually taken onshore. Deployment of floating lidars has occurred through various federally funded projects, but only encapsulates time periods of a couple of years at best. Private industry is also beginning to leverage floating lidars, but this data is often proprietary, and not shared with the general public. In this work, we make the case for a metocean reference site for long-term offshore wind energy. Specifically, we quantify the impact of having a metocean reference site compared to other methods of determining hub-height winds and energy production. We use an offshore floating lidar to directly measure the wind resource, and compare these measurements to predictions derived from other widely-available surface meteorological variables. These prediction methods (vertical extrapolation, machine learning, and NWP output) produce a variety of vertical wind speed profiles, of which produce different energy yield estimates for a reference offshore turbine (Figure 1). While some methods perform reasonably well against the lidar, the uncertainty in these energy yield estimates has financial implications, further illustrating the need for long-term measurements in coastal waters.

machine learning↗

Comprehensive GOM Federal Waters Platform, Incident, Metocean, and Geohazard Dataset

The dataset contains integrated data from an array of disparate data sources, all spatially and temporally linked to platforms in the federal waters of the Gulf of Mexico (platform data from BSEE, 2020). Integrated data includes past reported incidents dating back to 1956 (BSEE, BOEM, MMS), metocean data (see Nelson et al. in review for source information), and geohazard data (see Nelson et al. in review for source information). Proprietary well production information was redacted from this dataset, but was used in resulting analytics.

Full System↗

Holistic Marine Energy Resource Assessments: A Wave and Offshore Wind Perspective of Metocean Conditions

Offshore wind and wave energy resources are possibly the last significantly untapped renewable energy resource, and could play a significant role in mitigating the worst impacts of climate change via the generation of renewable electricity. However, offshore wind and wave energy resource assessments have been conducted as independent parallel processes, with little interaction with regard to best practices, lessons learnt, or opportunities to create compatible methodologies for future utilization by the broader marine energy sector. Based on the latest technical specifications from the International Electrotechnical Commission, and the highest fidelity publicly available datasets, the offshore wind and wave conditions at the PacWave site off Oregon, USA were quantified. The results clearly show a significant untapped energy resource an annual average wave energy flux of ~35kW/m and a mean average wind speed of 7.8m/s. The offshore wind and wave energy resources both show significant seasonal variation, with offshore wind also featuring a consistent daily profile during summer. Finally, opportunities and challenges associated with developing a holistic assessment of offshore marine energy resources were discussed and recommendations provided.

Robertson, Bryson↗

Observational Assessment of Metocean Conditions in the WFIP3 Region

The WFIP3 project, sponsored by the U.S. Department of Energy, is aimed at improving our understanding of the physics of the atmosphere and ocean that dictate the structure and variability of the wind resource within the MABL. As part of the project, a long-term offshore field campaign will take place along the U.S. East Coast to provide an unprecedented characterization of the MABL in the vicinity of the Massachusetts/Rhode Island wind energy lease areas. The unprecedented observational data set collected in the WFIP3 field campaign will allow intensive numerical modeling development and validation efforts. To inform the field campaign design and the preliminary studies associated with it, here we perform a characterization of the MABL and ocean conditions by leveraging available observations in the region.

lidars↗

Reference Site Conditions 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. In addition to providing curated reference site condition datasets for four U.S. areas, our assessment highlights the need for more publicly available metocean and soil condition data.

17 WIND ENERGY↗

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↗

IEA Wind Task 49: Reference Site Conditions for Floating Wind Arrays

The commercial-scale deployment of floating offshore wind (FOW) projects is expected to take place in a diverse range of sites that may differ significantly from existing fixed-bottom projects. FOW farms are particularly sensitive to the water depth and the meteorological and oceanographic (metocean) and geotechnical conditions at the project site due to the wave-induced system motions and loads as well as the anchoring system constraints imposed by the seafloor conditions. Uncertainty around the site conditions will permeate through all aspects of project design, leading to suboptimal and overly conservative designs, increased costs, and adversely affected performance. As FOW expands into a global industry, metocean and geotechnical conditions will increasingly vary for projects located in different geographic regions or in far-from-shore, deep-water sites. This study represents the outputs of work package 1 of International Energy Agency Wind Task 49, which focuses on the integrated design of floating wind arrays. The primary goal of this study is to establish the type of parameters and constraints required to characterize FOW array reference sites; provide a realistic and publicly available set of reference site conditions to the FOW community as a baseline set of data for individual research projects; identify and categorize any critical gaps in the existing data or methodologies required to define reference site characteristics; and inform and support the design of reference FOW arrays. A building block concept was developed for synthesizing reference sites for the design of FOW arrays. The building blocks include three classes of site conditions focusing on the techno-economic design of FOW projects: metocean conditions, seabed conditions, and coastal infrastructure. All reference site data produced and collected in this study are publicly available.

17 WIND ENERGY↗

Lidar Buoy Data Dictionary: For the 2020 – 2021 California Deployments

Pacific Northwest National Laboratory (PNNL) manages two AXYS WindSentinel™ buoys (Buoys #120 and #130) on behalf of the U.S. Department of Energy (DOE) that collect a comprehensive set of meteorological and oceanographic (metocean) data to support resource characterization for wind energy offshore. The buoys have been deployed off the California coast in partnership with the Bureau of Ocean Energy Management (BOEM) from September 2020 through October 2021. One buoy was deployed within the Morro Bay Call Area offshore central California; the other buoy was deployed within the Humboldt Call Area off the coast of northern California. The measurements from the buoys are used to characterize the metocean conditions near potential locations for offshore wind lease areas and are uploaded to DOE’s Data Archive and Portal (DAP). Plots are updated on the DAP webpage to visualize the recent metocean measurements. This document serves as a data dictionary – or reference guide – for understanding and interpreting the data available from the buoys. This document includes: (1) specifications for the buoy instrumentation (Section 2.0) (2) description of each plot and definition of measured parameters (Section 3.0) (3) description of data files and naming convention (Appendix A) (4) reference guide of measurements and variables (Appendix B).

17 WIND ENERGY↗

Gulf of Mexico Risk Analysis Database (GoMRAD)

The Gulf of Mexico Risk Analysis Database is comprehensive Esri geodatabase of vector layers, raster layers, and tables curated for risk analysis within the offshore Gulf of Mexico. Datasets include bathymetry, seafloor characteristics (channels, anomalies, faults, etc.), MetOcean data (wind speed, wave height, etc.), ocean current data, sediment data, and machine learning training regions used in NETL's Ocean & Geohazard Analysis (OGA) tool. This database serves as a compliment to the OGA tool by providing many of the datasets used in the design of the OGA tool, including regions used for machine learning. This database also serves as a valuable resource for risk analysis studies within the offshore Gulf of Mexico. This work was completed under the Advanced Offshore Research Portfolio, FWP Number: 1022476.

BOEM,Bathymetry,Gulf Of Mexico,Machine Learning,Me↗

Ocean & Geohazard Analysis Tool

The Ocean & Geohazard Analysis (OGA) software tool is designed to summarize insights into key offshore hazards drawing from a diverse set of approaches, including artificial intelligence, machine learning, probabilistic and statistical, and offshore data sources. The offshore hazards that can be analyzed include submarine landslides, extreme wind/wave/current event probabilities, earthquakes, and metocean pathways (CIAM Climatological Isolation and Attraction Model–Climatological Lagrangian Coherent Structures - Submissions - EDX (doe.gov)). Currently, the tool is developed for use in the Gulf of Mexico. The data underlying the offshore hazard analyses can be found here: https://edx.netl.doe.gov/dataset/gulf-of-mexico-risk-analysis-database-gomrad This work was conducted under the Advanced Offshore Research Portfolio, FWP Number 1022409 at National Energy Technology Laboratory, U.S. Dept. of Energy. Disclaimer This project was funded by the United States Department of Energy, National Energy Technology Laboratory, in part, through a site support contract. Neither the United States Government nor any agency thereof, nor any of their employees, nor the support contractor, nor any of their employees, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof.

AIML↗

Modeling and observations of North Atlantic cyclones: Implications for U.S. Offshore wind energy

To meet the Biden-Harris administration's goal of deploying 30 GW of offshore wind power by 2030 and 110 GW by 2050, expansion of wind energy into U.S. territorial waters prone to tropical cyclones (TCs) and extratropical cyclones (ETCs) is essential. This requires a deeper understanding of cyclone-related risks and the development of robust, resilient offshore wind energy systems. Here, this paper provides a comprehensive review of state-of-the-science measurement and modeling capabilities for studying TCs and ETCs, and their impacts across various spatial and temporal scales. We explore measurement capabilities for environments influenced by TCs and ETCs, including near-surface and vertical profiles of critical variables that characterize these cyclones. The capabilities and limitations of Earth system and mesoscale models are assessed for their effectiveness in capturing atmosphere–ocean–wave interactions that influence TC/ETC-induced risks under a changing climate. Additionally, we discuss microscale modeling capabilities designed to bridge scale gaps from the weather scale (a few kilometers) to the turbine scale (dozens to a few meters). We also review machine learning (ML)-based, data-driven models for simulating TC/ETC events at both weather and wind turbine scales. Special attention is given to extreme metocean conditions like extreme wind gusts, rapid wind direction changes, and high waves, which pose threats to offshore wind energy infrastructure. Finally, the paper outlines the research challenges and future directions needed to enhance the resilience and design of next-generation offshore wind turbines against extreme weather conditions.

17 WIND ENERGY↗

Conceptual Design of a Tension Leg Platform With 22.3 MW Vertical Axis Turbine

Here, this paper presents the conceptual design of a tension leg platform (TLP) for the ARCUS “towerless” vertical-axis wind turbine (VAWT). VAWTs are ideal for floating offshore sites and have several advantages over horizontal-axis wind turbines (HAWT) including reduced top mass, lower center of gravity, increased energy capture, and in turn lower cost. The towerless ARCUS VAWT drives these advantages further through increased structural efficiency and by enabling more optimized TLP designs with simplified installation procedures. For hull sizing, we have studied three turbine sizes with corresponding power ratings of 5.1 MW, 10.4 MW and 22.3 MW. The largest turbine was identified as having the greatest potential to reduce the levelized cost of energy (LCOE) and is the reference size used for the further detailed design process. The conceptual design of the VAWT TLP has been awarded with an ABS Approval in Principle Certificate. This paper contains brief analysis results and design findings for a TLP designed to house a VAWT, including the following topics: • Applicable Design Codes • Metocean Conditions • ARCUS Turbine Loads • Design Load Cases and Requirements - Pre-service TLP Stability - In-place TLP Global Performance • Platform Configurations, Hull Structure Scantling Design, Weight and CG Estimation, and General Arrangement Drawings • Hull Ballast Plan for both Pre-service and In-place Conditions • Pre-service Quayside Integration, Transportation and Wet Tow Stability Analysis • Global Performance Analysis for Motions and Tendon tensions • Summary of cost components and system levelized cost of energy

17 WIND ENERGY↗

A Study on Modeled Wind Speed Errors Using the U.S. Department of Energy Buoys

Pacific Northwest National Laboratory (PNNL) operates two AXYS WindSentinel lidar buoys for the U.S. Department of Energy’s Wind Energy Technologies Office. The purpose of these buoys is to collect hub-height winds and supporting meteorological and oceanographic information to facilitate the development of wind energy in the U.S. waters. The first deployment for one buoy was off the coast of Virginia from December 2014 to May 2016, and the first deployment for the other buoy was off the coast of New Jersey from November 2015 until February 2017. This report describes recent analysis of data collected during these first two deployments. Specifically, we compare hub-height wind speed estimates using Monin-Obukhov Similarity Theory (MOST) to the lidar measurements, and examine how those errors are affected by wind direction, atmospheric stability, wind-wave direction differences, and various measures of the wave-state. The comparisons are done using standard similarity functions based on MOST; including the Businger - Dyer, the Beljaars & Holtslag and the Vickers & Mahrt similarity functions. All models produce large errors over the range of atmospheric stabilities that were observed, with the largest errors occurring for stable flows. The Vickers & Mahrt function resulted in the largest overall bias and standard deviation, while Beljaars & Holtslag function gave the smallest bias and standard deviation due to its better performance under stable conditions. The models perform best under unstable conditions, but even in this regime there is a consistent overestimation of the wind speed of between roughly 0 to 1 ms -1 compared to the lidar measurements. We identify specific metocean conditions (i.e. stability and wind and wave directions) at each of the deployment locations that lead to large errors in MOST predictions. Finally, a coupled ocean-atmosphere model framework was investigated to simulate large errors in weather research forecasting (WRF).

17 WIND ENERGY↗