Classifying rotor‐layer wind to reduce offshore available power uncertainty

Pé, Alexandra St.; Sperling, Meredith; Brodie, Joseph F.; Delgado, Rubén

doi:10.1002/we.2159

Cited by 9 publications

(3 citation statements)

References 28 publications

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“…Actual observations of wind shear and veer exhibit a significant variety of shapes (Pé et al, 2018), as shown in Figure 1, with four wind speed profiles from vertically profiling Doppler lidar and relevant idealized linear and logarithmic profiles.…”

Section: Introductionmentioning

confidence: 99%

How wind speed shear and directional veer affect the power production of a megawatt-scale operational wind turbine

Murphy¹,

Lundquist²,

Fleming³

2019

Preprint

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Abstract. Most megawatt-scale wind turbines align themselves into the wind as defined by the wind speed at or near the center of the rotor (hub height). However, both wind speed and wind direction can change with height across the area swept by the turbine blades. A turbine aligned to hub-height winds might experience suboptimal or superoptimal power production, depending on the changes in the vertical profile of wind, or shear. Using observed winds and power production over 6 months at a site in the high plains of North America, we quantify the sensitivity of a wind turbine's power production to wind speed shear and directional veer as well as atmospheric stability. We measure shear using metrics such as α (the log-law wind shear exponent), βbulk (a measure of bulk rotor-disk-layer veer), βtotal (a measure of total rotor-disk-layer veer) and rotor-equivalent wind speed (REWS), a measure of actual momentum encountered by the turbine by accounting for shear). We also consider the REWS with the inclusion of directional veer, REWSθ, although statistically significant differences in power production do not occur between REWS and REWSθ at our site. When REWS differs from the hub-height wind speed (as measured either by the lidar or a transfer function-corrected nacelle anemometer), the turbine power generation also differs from the mean power curve in a statistically significant way. This change in power can be more than 70 kW, or up to 5 % of the rated power for a single 1.5-MW utility-scale turbine. Over a theoretical 100-turbine wind farm, these changes could lead to instantaneous power prediction gains or losses equivalent to the addition or loss of multiple utility-scale turbines. At this site, REWS is the most useful metric for segregating the turbine's power curve into high and low cases of power production when compared to the other shear or stability metrics. Therefore, REWS enables improved forecasts of power production.

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Section: Introductionmentioning

confidence: 99%

How wind speed shear and directional veer affect the power production of a megawatt-scale operational wind turbine

Murphy¹,

Lundquist²,

Fleming³

2019

Preprint

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show abstract

“…The wind speed provided by Equation () is effectively a rotor‐average wind speed (also known as rotor‐equivalent or rotor‐layer wind speed), which is a better representation of the wind speed experienced by the entire rotor than the wind speed at the exact location of the hub, and ultimately provides a better estimate of the power production of the turbine 31,32 …”

Section: Methodsmentioning

confidence: 99%

Comparison of individual versus ensemble wind farm parameterizations inclusive of sub‐grid wakes for the WRF model

Archer

Vasel-Be-Hagh

2022

Wind Energy

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Wind turbine wakes can be predicted somewhat accurately with mesoscale numerical models, such as the Weather Research and Forecast (WRF) model, via a wind farm parameterization (WFP) that treats the effects of the wakes, which are sub‐grid features, on power production and the environment. A few WFPs have been proposed in the literature, but none has been able to properly account for the individual wakes within a grid cell or the effects of overlapping wakes from multiple turbines. A solution to these two issues is a WFP that includes both a wake model, which is a simplified analytical model of the wind speed (or wind power) deficit caused by a wake, and a wake superposition model, which accounts for overlapping wakes. Several such WFPs are developed here for the WRF model—based on the Jensen, the Geometric, and the Gaussian wake models coupled with two wake superposition methods (based on a squared deficit and a squared velocity superposition)—and tested individually, as well as combined together in an ensemble (EWFP), at two modern offshore wind farms. Most WFPs perform satisfactorily alone, but the EWFP generally outperforms them at both farms. The issue of resolved versus sub‐grid wakes is explored for single‐ and multi‐cell cases and for directions of alignment and non‐alignment between the wind direction and the turbine columns. Although different combinations of wake loss and wake superposition models might be preferred at other wind farms, the general findings and detailed performance statistics given here might provide useful guidance in their selection.

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“…It is well known that winds flowing at a velocity v, sweep through the blade A and increase with the cube of its velocity. The power density is expressed as using the following equation [40].…”

Section: The System Of Wind Power Potential To Produce Hydrogenmentioning

confidence: 99%

Assessment of Wind Energy Potential for the Production of Renewable Hydrogen in Sindh Province of Pakistan

et al. 2019

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In this study, we developed a new hybrid mathematical model that combines wind-speed range with the log law to derive the wind energy potential for wind-generated hydrogen production in Pakistan. In addition, we electrolyzed wind-generated power in order to assess the generation capacity of wind-generated renewable hydrogen. The advantage of the Weibull model is that it more accurately reflects power generation potential (i.e., the capacity factor). When applied to selected sites, we have found commercially viable hydrogen production capacity in all locations. All sites considered had the potential to produce an excess amount of wind-generated renewable hydrogen. If the total national capacity of wind-generated was used, Pakistan could conceivably produce 51,917,000.39 kg per day of renewable hydrogen. Based on our results, we suggest that cars and other forms of transport could be fueled with hydrogen to conserve oil and gas resources, which can reduce the energy shortfall and contribute to the fight against climate change and global warming. Also, hydrogen could be used to supplement urban energy needs (e.g., for Sindh province Pakistan), again reducing energy shortage effects and supporting green city programs.

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Classifying rotor‐layer wind to reduce offshore available power uncertainty

Cited by 9 publications

References 28 publications

How wind speed shear and directional veer affect the power production of a megawatt-scale operational wind turbine

How wind speed shear and directional veer affect the power production of a megawatt-scale operational wind turbine

Comparison of individual versus ensemble wind farm parameterizations inclusive of sub‐grid wakes for the WRF model

Assessment of Wind Energy Potential for the Production of Renewable Hydrogen in Sindh Province of Pakistan

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