Impacts of the Low-Level Jet's Negative Wind Shear on the Wind Turbine

Gutierrez, Walter; Ruiz-Columbie, Arquimedes; Tutkun, Murat; Castillo, Luciano

doi:10.5194/wes-2017-22

Cited by 10 publications

(11 citation statements)

References 20 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…12c). While previous work (Gutierrez et al, 2017) has found that negative shear can decrease loads on the wind turbine system (primarily at the nacelle and tower), the positive shear in these profiles has been directly linked to an increase in static and dynamic loads relative to a well-mixed profile (Gutierrez et al, 2016). A recent study (Gutierrez et al, 2019) investigated the symmetry in wind turbine loads when the rotor experiences half-positive and half-negative shear and found complex interplay between the tower, blades and gravitational loads.…”

Section: Low-level Jetsmentioning

confidence: 98%

“…When the nose of the jet is within the rotor-swept area, a portion of the rotor will experience negative shear. Here, we quantify how much of the rotor experiences negative vs. positive shear for each LLJ profile using the turbine-jet relative distance parameter (ξ ; Gutierrez et al, 2017Gutierrez et al, , 2019. These values are shown in Fig.…”

Section: Low-level Jetsmentioning

confidence: 99%

“…Extreme wind events relevant to wind turbine operation include rapid changes in flow direction and speed or persistently high values of shear and veer (Commission, 2019). High vertical wind shear is of particular interest to wind en- ergy as it has a direct effect on wind turbine power and reliability (Colle and Novak, 2010;Peña et al, 2012;Dvorak et al, 2013;Gutierrez et al, 2014Gutierrez et al, , 2017Gutierrez et al, , 2019Murphy et al, 2020;Borvarán et al, 2020;Hallgren et al, 2020). One phenomenon responsible for producing highshear events has gained particular attention by the wind energy community: the low-level jet (LLJ), defined as local wind speed maximum in the lower 1000 m of the atmosphere (Soares et al, 2014).…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Extreme wind shear events in US offshore wind energy areas and the role of induced stratification

et al. 2021

View full text Add to dashboard Cite

Abstract. As the offshore wind industry emerges on the US East Coast, a comprehensive understanding of the wind resource – particularly extreme events – is vital to the industry's success. Such understanding has been hindered by a lack of publicly available wind profile observations in offshore wind energy areas. However, the New York State Energy Research and Development Authority recently funded the deployment of two floating lidars within two current lease areas off the coast of New Jersey. These floating lidars provide publicly available wind speed data from 20 to 200 m height with a 20 m vertical resolution. In this study, we leverage a year of these lidar data to quantify and characterize the frequent occurrence of high-wind-shear and low-level-jet events, both of which will have a considerable impact on turbine operation. In designing a detection algorithm for these events, we find that the typical, non-dimensional power-law-based wind shear exponent is insufficient to identify many of these extreme, high-wind-speed events. Rather, we find that the simple vertical gradient of wind speed better captures the events. Based on this detection method, we find that almost 100 independent events occur throughout the year with mean wind speed at 100 m height and wind speed gradient of 16 m s−1 and 0.05 s−1, respectively. The events have strong seasonal variability, with the highest number of events in summer and the lowest in winter. A detailed analysis reveals that these events are enabled by an induced stable stratification when warmer air from the south flows over the colder mid-Atlantic waters, leading to a positive air–sea temperature difference.

show abstract

Section: Low-level Jetsmentioning

confidence: 98%

Section: Low-level Jetsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Extreme wind shear events in US offshore wind energy areas and the role of induced stratification

et al. 2021

View full text Add to dashboard Cite

show abstract

“…As depicted in Fig. 1, LLJs at, above and below these altitudes have the potential to impact the wind speed, turbulence and shear across typical wind turbine rotor planes, and analyses of both observational data and Weather Research and Forecasting (WRF) simulations indicate that LLJs frequently occur at heights that interact with the rotor plane (Gutierrez et al, 2014(Gutierrez et al, , 2017Nunalee and Basu, 2014;Wagner et al, 2019;Aird et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

WRF-simulated low-level jets over Iowa: characterization and sensitivity studies

et al. 2021

View full text Add to dashboard Cite

Abstract. Output from 6 months of high-resolution simulations with the Weather Research and Forecasting (WRF) model are analyzed to characterize local low-level jets (LLJs) over Iowa for winter and spring in the contemporary climate. Low-level jets affect rotor plane aerodynamic loading, turbine structural loading and turbine performance, and thus accurate characterization and identification are pertinent. Analyses using a detection algorithm wherein the wind speed above and below the jet maximum must be below 80 % of the jet wind speed within a vertical window of approximately 20–530 m a.g.l. (above ground level) indicate the presence of an LLJ in at least one of the 14 700 4 km×4 km grid cells over Iowa on 98 % of nights. Nocturnal LLJs are most frequently associated with stable stratification and low turbulent kinetic energy (TKE) and hence are more frequent during the winter months. The spatiotemporal mean LLJ maximum (jet core) wind speed is 9.55 m s−1, and the mean height is 182 m. Locations of high LLJ frequency and duration across the state are seasonally varying, with a mean duration of 3.5 h. The highest frequency occurs in the topographically complex northwest of the state in winter and in the flatter northeast of the state in spring. Sensitivity of LLJ characteristics to the (i) LLJ definition and (ii) vertical resolution at which the WRF output is sampled is examined. LLJ definitions commonly used in the literature are considered in the first sensitivity analysis. These sensitivity analyses indicate that LLJ characteristics are highly variable with definition. Use of different definitions identifies both different frequencies of LLJs and different LLJ events. Further, when the model output is down-sampled to lower vertical resolution, the mean jet core wind speed height decreases, but spatial distributions of regions of high frequency and duration are conserved. Implementation of a polynomial interpolation to extrapolate down-sampled output to full-resolution results in reduced sensitivity of LLJ characteristics to down-sampling.

show abstract

“…Low-level jets modify wind power performance and loading by impacting wake recovery rates and vertical profiles of wind speed, direction and turbulence (Wharton and Lundquist, 2012;Bhaganagar and Debnath, 2014;Park et al, 2014;Gutierrez et al, 2017). Thus, for a complete assessment of loads and power, it is important to have a broad understanding of the site-specific low-level jet characteristics: how often do they the spatial and temporal variability of the coastal jets we refer to Ranjha et al (2013) and Lima et al (2018), who presented global maps based on reanalysis data.…”

Section: Introductionmentioning

confidence: 99%

Characterisation of offshore winds for energy applications

Kalverla

View full text Add to dashboard Cite

Offshore wind energy is regarded as one of the main ingredients of a sustainable energy system. A popular scenario for 2050 describes a stunning fleet of twenty-five thousand wind turbines that is to be installed in the North Sea. Obviously, the realisation of such a grand vision requires realistic estimates of the expected energy production, optimal wind farm layouts, and lifetime of various turbine designs. A wide range of computer models is used to simulate, for example, the interaction between the wind and the turbines. As inputs, they require (climatological) information about the wind field. An inherent property of model simulations and associated predictions is that they come with uncertainties. There is always a chance that reality will deviate from the anticipated course. Since offshore wind projects require large investments, these uncertainties naturally transform into financial risks. Therefore, a growing interest emerges in uncertainty quantification and reduction. This thesis addresses uncertainties that originate from the representation of the offshore wind field in the aforementioned engineering models. This goal is partly achieved through crossvalidation between available observations, output from meteorological models, and combined products of observations and meteorological model simulations that are known as reanalysis datasets. Additionally, the thesis reflects on the impact of (over)simplifications that are commonly used to reduce computational demands. Standard inflow specifications for engineering models have been built around highly idealized descriptions of the wind, such as the Weibull distribution, the logarithmic wind profile, and the 'wind rose'. With the growth of individual wind turbines, offshore wind projects, and the corresponding investments, these simplified descriptions are becoming inadequate. Moreover, contemporary design standards consider conditions of extreme winds, extreme shear, wind gusts, etcetera in an abstract statistical fashion that does not reflect the physical nature of these events. Chapter 1 further elaborates on the different models, data sources, assumptions and simplifications, and uncertainties.

show abstract

Impacts of the Low-Level Jet's Negative Wind Shear on the Wind Turbine

Cited by 10 publications

References 20 publications

Extreme wind shear events in US offshore wind energy areas and the role of induced stratification

Extreme wind shear events in US offshore wind energy areas and the role of induced stratification

WRF-simulated low-level jets over Iowa: characterization and sensitivity studies

Characterisation of offshore winds for energy applications

Contact Info

Product

Resources

About