Power and Wind Shear Implications of Large Wind Turbine Scenarios in the US Central Plains

Barthelmie, R.J.; Shepherd, Tristan J.; Aird, Jeanie A.; Pryor, Sara C.

doi:10.3390/en13164269

Cited by 23 publications

(12 citation statements)

References 49 publications

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“…In particular, the power production of a wind turbine has a very complex dependence on ambient conditions [7][8][9][10], on the stochastic nature of the source [11,12], on the working parameters [13,14], on the wake interactions [15,16], and on the health status and on the efficiency [17,18] of the sub-components. On these grounds, it is a common sense expectation that the efficiency of wind turbines declines with age, but there are no standards about how much and in how much time the performance should decline.…”

Section: Introductionmentioning

confidence: 99%

Estimation of the Performance Aging of the Vestas V52 Wind Turbine through Comparative Test Case Analysis

Astolfi¹,

Byrne²,

Castellani³

2021

Energies

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It is a common sense expectation that the efficiency of wind turbines should decline with age, similarly to what happens with most technical systems. Due to the complexity of this kind of machine and the environmental conditions to which it is subjected, it is far from obvious how to reliably estimate the impact of aging. In this work, the aging of five Vestas V52 wind turbines is analyzed. The test cases belong to two different sites: one is at the Dundalk Institute of Technology in Ireland, and four are sited in an industrial wind farm in a mountainous area in Italy. Innovative data analysis techniques are employed: the general idea consists of considering appropriate operation curves depending on the working control region of the wind turbines. When the wind turbine operates at fixed pitch and variable rotational speed, the generator speed-power curve is studied; for higher wind speed, when the rotational speed has saturated and the blade pitch is variable, the blade pitch-power curve is considered. The operation curves of interest are studied through the binning method and through a support vector regression with a Gaussian kernel. The wind turbine test cases are analyzed vertically (each in its own history) and horizontally, by comparing the behavior at the two sites for the given wind turbine age. The main result of this study is that an evident effect of aging is the worsening of generator efficiency: progressively, less power is extracted for the given generator rotational speed. Nevertheless, this effect is observed to be lower for the wind turbines in Italy (order of −1.5% at 12 years of age with respect to seven years of age) with respect to the Dundalk wind turbine, which shows a sharp decline at 12 years of age (−8.8%). One wind turbine sited in Italy underwent a generator replacement in 2018: through the use of the same kind of data analysis methods, it was possible to observe that an average performance recovery of the order of 2% occurs after the component replacement. It also arises that for all the test cases, a slight aging effect is visible for higher wind speed, which can likely be interpreted as due to declining gearbox efficiency. In general, it is confirmed that the aging of wind turbines is strongly dependent on the history of each machine, and it is likely confirmed that the technology development mitigates the effect of aging.

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Section: Introductionmentioning

confidence: 99%

Estimation of the Performance Aging of the Vestas V52 Wind Turbine through Comparative Test Case Analysis

Astolfi¹,

Byrne²,

Castellani³

2021

Energies

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“…Second is that phenomena outside the surface boundary layer (such as low level jets) influence hub height wind speed trends but would not be reflected in observations of surface winds. 9 We suggest that until the relationship between observed surface wind speeds and wind plant wind speeds is more fully understood, caution should be taken when using surface wind speed observations to draw conclusions about long-term wind energy potential.…”

Section: Comparison Of Interannual Variation At Meteorological Statio...mentioning

confidence: 96%

“…In particular, there are questions about whether this process is appropriate given evidence of a disconnect between surface and hub-height wind speeds (e.g., rotor tips can extend beyond the atmospheric surface layer) and the often sizeable horizontal distance between observation stations and wind plants. [9][10][11] Our analysis addresses a research gap: to date, empirical analyses that compare interannual wind speed variation at surface meteorological stations to data at active wind plants (at hub-height) have been limited due to the challenges listed above. Our use of generation records allows us to address this research gap with data produced and recorded by wind plants themselves.…”

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confidence: 99%

What can surface wind observations tell us about interannual variation in wind energy output?

2022

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The past decade of wind power growth was supported by capacity factor improvements and associated cost reductions. But are higher capacity factors a technology success story or, as suggested by recent research, has the influence of technology been overstated by ignoring positive surface wind speed trends? The answer could influence estimates of wind energy's cost and even future deployment rates. We find that US surface wind speed observations imply a 2.6% improvement in capacity factors from 2010 to 2019. Yet newer vintages of wind plants have recorded capacity factors that are 25% larger than plants built close to 2010. It follows that technological factors and improved site quality, not higher wind speeds, drove most of the improvement in capacity factors. Additionally, we match hundreds of meteorological stations to nearby (<25 km) wind plants and compare annual estimated generation, based on a function of surface wind speed observations, to annual recorded generation. Researchers rely on this publicly available surface data because measurements co-located with wind plants are generally considered proprietary. Our analysis addresses a research gap: interannual variation in observed surface wind speeds is rarely compared to observed data at wind plant locations and turbine heights. We find that despite its common use for this purpose, generation estimates based on publicly available surface observational data provide a poor proxy for interannual variability in recorded wind generation. These findings suggest that caution is generally needed when researchers use surface wind speed measurements to investigate longterm wind energy trends.

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“…Further, the increasing physical dimensions of wind turbine heights over time, and particularly offshore, mean LLJs may more frequently intersect with the wind turbine rotor plane [24,25]. When a LLJ occurs within the rotor plane, changes to the distributions of turbulent kinetic energy, shear, wind speed and wind direction [26,27] may increase energy production and enhance wind turbine wake recovery [28,29]. However, it is also likely to be associated with enhanced static and mechanical loading, fatigue cycles and deflections [30].…”

Section: Introductionmentioning

confidence: 99%

Occurrence of Low-Level Jets over the Eastern U.S. Coastal Zone at Heights Relevant to Wind Energy

et al. 2022

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Two years of high-resolution simulations conducted with the Weather Research and Forecasting (WRF) model are used to characterize the frequency, intensity and height of low-level jets (LLJ) over the U.S. Atlantic coastal zone. Meteorological conditions and the occurrence and characteristics of LLJs are described for (i) the centroids of thirteen of the sixteen active offshore wind energy lease areas off the U.S. east coast and (ii) along two transects extending east from the U.S. coastline across the northern lease areas (LA). Flow close to the nominal hub-height of wind turbines is predominantly northwesterly and southwesterly and exhibits pronounced seasonality, with highest wind speeds in November, and lowest wind speeds in June. LLJs diagnosed using vertical profiles of modeled wind speeds from approximately 20 to 530 m above sea level exhibit highest frequency in LA south of Massachusetts, where LLJs are identified in up to 12% of hours in June. LLJs are considerably less frequent further south along the U.S. east coast and outside of the summer season. LLJs frequently occur at heights that intersect the wind turbine rotor plane, and at wind speeds within typical wind turbine operating ranges. LLJs are most frequent, intense and have lowest core heights under strong horizontal temperature gradients and lower planetary boundary layer heights.

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Power and Wind Shear Implications of Large Wind Turbine Scenarios in the US Central Plains

Cited by 23 publications

References 49 publications

Estimation of the Performance Aging of the Vestas V52 Wind Turbine through Comparative Test Case Analysis

Estimation of the Performance Aging of the Vestas V52 Wind Turbine through Comparative Test Case Analysis

What can surface wind observations tell us about interannual variation in wind energy output?

Occurrence of Low-Level Jets over the Eastern U.S. Coastal Zone at Heights Relevant to Wind Energy

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