2016 Offshore Wind Energy Resource Assessment for the United States

Musiał, W.; Heimiller, D.; Beiter, Philipp; Scott, G.; Draxl, Caroline

doi:10.2172/1324533

Cited by 137 publications

(207 citation statements)

References 13 publications

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“…In the United States, only a single 30 MW commercial offshore wind farm (Deepwater Wind, 2016) has been built. However, the U.S. offshore technical resource potential is estimated to be nearly double the nation's current electricity use (Musial et al, 2016). Many offshore wind projects are currently being planned, mostly concentrated along the Eastern Seaboard.…”

Section: Introductionmentioning

confidence: 99%

Offshore Wind Turbines Will Encounter Very Low Atmospheric Turbulence

Bodini¹,

Lundquist²,

Kirincich³

2020

J. Phys.: Conf. Ser.

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Key Points:• strength and persistence of wind plant wakes depends on turbulence dissipation rate • turbulence dissipation rate offshore is small with a weak diurnal cycle • dissipation rate is larger when flow is from the land, which tends to be in wintertime at this site AbstractThe rapid growth of offshore wind energy requires accurate modeling of the wind resource, which can be depleted by wind farm wakes. Turbulence dissipation rate ( ) governs the accuracy of model predictions of hub-height wind speed and the development and erosion of wakes. Here we assess the variability of turbulence kinetic energy and using 13 months of observations from a profiling lidar deployed on a platform off the Massachusetts coast. Offshore, is 2 orders of magnitude smaller than onshore, with a subtle diurnal cycle. Wind direction largely influences the annual cycle of turbulence, with larger values in winter when the wind flows from the land, and smaller values in summer, when the wind is mainly from open ocean. Because of the weak turbulence, wind plant wakes will be stronger and persist farther downwind in summer.

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Section: Introductionmentioning

confidence: 99%

Offshore Wind Turbines Will Encounter Very Low Atmospheric Turbulence

Bodini¹,

Lundquist²,

Kirincich³

2020

J. Phys.: Conf. Ser.

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“…The simulations, using proprietary modeling software, were run in a nested configuration, down to 1‐km resolution, with downscaling to 200‐m resolution, to derive a wind dataset at 90‐m AGL. A more recent effort combined this dataset with the Wind Integration National Dataset (WIND) Toolkit to derive a wind climatology at 100‐m AGL out to 200 nautical miles offshore.…”

Section: Introductionmentioning

confidence: 99%

Offshore wind speed estimates from a high‐resolution rapidly updating numerical weather prediction model forecast dataset

2017

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In association with the Department of Energy–funded Position of Offshore Wind Energy Resources (POWER) project, we present results from compositing a 3‐year dataset of 80‐m (above ground level) wind forecasts from the 3‐km High‐Resolution Rapid Refresh (HRRR) model over offshore regions for the contiguous United States. The HRRR numerical weather prediction system runs once an hour and features hourly data assimilation, providing a key advantage over previous model‐based offshore wind datasets. On the basis of 1‐hour forecasts from the HRRR model, we highlight the different climatological regimes of the nearshore environment, characterizing the mean 80‐m wind speed as well as the frequency of exceeding 4, 12, and 25 m s−1 for east and west coast, Gulf of Mexico, and Great Lake locations. Preliminary verification against buoy measurements demonstrates good agreement with observations. This dataset can inform the placement of targeted measurement systems in support of improving resource assessments and wind forecasts to advance offshore wind energy goals both in New England and other coastal regions of the United States.

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“…Using the global areas from [37] and the US areas from [38], we estimate the annual energy production of each area from its average wind speed assuming a Weibull distribution of annual wind speeds [see 37, 39, 47 for discussion] and a capacity density of 5 MW km −2 [4,[37][38][39]. We use the water depth and distance from shore to determine the appropriate capital cost and operation and maintenance (O&M) cost for each area [41,42].…”

Section: Methodsmentioning

confidence: 99%

The global climate value of offshore wind energy

Cranmer

Baker

2020

Environ. Res. Lett.

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We estimate the climate value of offshore wind energy with a highly flexible, forward-looking method that estimates the value in a consistent manner under a range of policies, including carbon caps and taxes. Backward looking methods measure the damages avoided due to emissions reductions attributed to renewable energy under an existing policy structure. Under a carbon cap, however, the climate value of offshore wind energy comes entirely from reducing the cost of meeting the cap. Our method for estimating the prospective climate value compares both climate damages and abatement costs in cases with and without offshore wind energy. This climate value can be compared to the costs of reducing barriers to new technologies, such as streamlining approval processes. The climate value depends on the cost of offshore wind technology, the climate policy under consideration, the severity of damages from climate change, and the discount rate. In the absence of a binding climate policy, the climate value of offshore wind energy ranges from $246 billion to $2.5 trillion under central assumptions about damages and discount rate, and can reach over $30 trillion under certain assumptions (low discount rate, high damages, low technology costs). The value of technical changeof moving from the highest cost to lowest cost assumptions about the technology-is estimated to be $300 billion even under the most unfavorable assumptions, dwarfing worldwide R&D investment in all wind energy technology. Using this method, we find that new low carbon technologies can provide a hedge against uncertainty and error in climate policies.

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2016 Offshore Wind Energy Resource Assessment for the United States

Cited by 137 publications

References 13 publications

Offshore Wind Turbines Will Encounter Very Low Atmospheric Turbulence

Offshore Wind Turbines Will Encounter Very Low Atmospheric Turbulence

Offshore wind speed estimates from a high‐resolution rapidly updating numerical weather prediction model forecast dataset

The global climate value of offshore wind energy

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