Hurricane risk assessment of offshore wind turbines

Hallowell, Spencer T.; Myers, Andrew C.; Arwade, Sanjay R.; Pang, Weichiang; Rawal, Prashant; Hines, Eric M.; Hajjar, Jerome F.; Qiao, Chi; Valamanesh, V.; Wei, Kai; Carswell, Wystan; Fontana, Casey M.

doi:10.1016/j.renene.2018.02.090

Cited by 70 publications

(38 citation statements)

References 33 publications

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“…Offshore wind turbines in the LA along with the U.S. east coast will be at risk from extreme wind and wave conditions including those associated with Atlantic hurricanes (and other tropical cyclones) [25]. However, considerable uncertainty surrounds the hurricane catastrophic risk to offshore wind power off the U.S. east coast [26][27][28]. Analyses using the HURDAT Hurricane reanalysis database [29] for the period 1899-2004 were used to infer 50-year return period wind speed of 59 ms −1 for coastal areas along the U.S. east coast, although only four years during the 106 year record had intensity estimates anywhere in the region of the 16 LA with wind speeds in excess of this level [30].…”

Section: Research Objectivesmentioning

confidence: 99%

Extreme Wind and Waves in U.S. East Coast Offshore Wind Energy Lease Areas

et al. 2021

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The Outer Continental Shelf along the U.S. east coast exhibits abundant wind resources and is now a geographic focus for offshore wind deployments. This analysis derives and presents expected extreme wind and wave conditions for the sixteen lease areas that are currently being developed. Using the homogeneous ERA5 reanalysis dataset it is shown that the fifty-year return period wind speed (U50) at 100 m a.s.l. in the lease areas ranges from 29.2 to 39.7 ms−1. After applying corrections to account for spectral smoothing and averaging period, the associated pseudo-point U50 estimates are 34 to 46 ms−1. The derived uncertainty in U50 estimates due to different distributional fitting is smaller than the uncertainty associated with under-sampling of the interannual variability in annual maximum wind speeds. It is shown that, in the northern lease areas, annual maximum Swind speeds are generally associated with intense extratropical cyclones rather than cyclones of tropical origin. Extreme wave statistics are also presented and indicate that the 50-year return period maximum wave height may substantially exceed 15 m. From this analysis, there is evidence that annual maximum wind speeds and waves frequently derive from the same cyclone source and often occur within a 6 h time interval.

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Section: Research Objectivesmentioning

confidence: 99%

Extreme Wind and Waves in U.S. East Coast Offshore Wind Energy Lease Areas

et al. 2021

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“…Further research to understand how both natural climate variability and human-caused climate change will affect wind resources is needed to reduce risk to the financial investments made to deploy wind plants based on resource assessments. Given the increasing deployments of wind plants in locations vulnerable to extreme events like hurricanes (Hallowell et al 2018) that will be affected by climate variability, assessments of the impacts of these extreme events on turbine-relevant atmospheric parameters (Worsnop et al 2017) will become more important.…”

Section: Breakout Group 1: Atmospheric Science and Forecastingmentioning

confidence: 99%

IEA Wind TCP: Results of IEA Wind TCP Workshop on a Grand Vision for Wind Energy Technology

Dykes

Veers

Lantz

et al. 2019

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Research advanced erosion-resistant composite materials for use on the leading edge of wind turbine blades Research, development, and scale-up of thermoplastic resin systems to reduce wind turbine blade manufacturing cycle times, reduce blade costs, enable thermal welding of bond lines, increase recyclability, and enable advanced in-field blade repair techniques Research advanced thermoset materials that can be recovered and reused Research metals and other noncomposite materials for development of lightweight, high-strength, and high-stiffness turbine components Grand Challenge 2: Automation Develop comprehensive techno-economic models for automation and a virtual factory (or digital twin of a factory) to understand advantages and disadvantages of targeted automation for both wind turbine blade molding and finishing operations Identify and quantify all cost inputs for wind turbine component manufacturing (e.g., blades, towers) to identify production steps that would benefit from automation Develop automated production methods for the continuous manufacturing of one-piece wind turbine towers for on-site manufacturing Develop advanced design tools to optimize blade and tower design with respect to manufacturing with automation Research and develop automation technology able to locate complex wind turbine blade geometry in space to allow for effective automated finishing operations, such as sanding, drilling, and cutting Develop methods to automate the delivery, placement, and inspection of core material into blade skin molds during the composite laminate skin lay-up Integrate real-time inspection and quality control into automated production steps for wind turbine blades, towers, and other components Develop large-scale, low-cost, high-throughput, high-performance automated additive manufacturing technologies (e.g., 3D printing, automated fiber placement and tape layup, filament winding) for the production of towers, blade skins, blade spars, and other turbine components Develop embedded metrology and out-of-mold indexing technologies Grand Challenge 3: On-Site Manufacturing Develop robust composite materials for use in broad on-site environmental conditions Research the chemistry and processing of in-situ thermoplastic resin systems to enable thermally welded joints in an on-site manufacturing environment Develop targeted wind turbine blade finishing automation techniques designed to reduce the overall footprint of on-site finishing operations and minimize production facility floor space Research additive manufacturing to print wind turbine blade molds and tooling at on-site manufacturing locations IEA Wind TCP Task 11

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“…For instance, accurate assessment of risk due to hurricanes and other extreme events requires engineers and atmospheric scientists to work together to determine the meteorological phenomena that are relevant to system level risk (Yu et al 2012, Fraudenreich et al 2014, Dibra et al 2016, Kim et al 2016, Hallowell et al 2018). …”

Section: Support Multidisciplinary Researchmentioning

confidence: 99%

Reaching convergence in United States offshore wind energy research : a multidisciplinary framework for innovation, a white paper authored by the Massachusetts Research Partnership in Offshore Wind

Power-Us¹

2018

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SynopsisThis white paper proposes a framework for offshore wind research and innovation in the United States which establishes the relationships, data, systems-level thinking, and strategic research approaches needed to advance the global offshore wind industry. As the nation enters a market that has matured substantially in Europe and is growing quickly in Asia, a well-coordinated, reliably funded approach to research can help secure U.S. stewardship of its natural resources and strengthen U.S. competitiveness in the global market.

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Hurricane risk assessment of offshore wind turbines

Cited by 70 publications

References 33 publications

Extreme Wind and Waves in U.S. East Coast Offshore Wind Energy Lease Areas

Extreme Wind and Waves in U.S. East Coast Offshore Wind Energy Lease Areas

IEA Wind TCP: Results of IEA Wind TCP Workshop on a Grand Vision for Wind Energy Technology

Reaching convergence in United States offshore wind energy research : a multidisciplinary framework for innovation, a white paper authored by the Massachusetts Research Partnership in Offshore Wind

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