Time-Dependent Upper Limits to the Performance of Large Wind Farms Due to Mesoscale Atmospheric Response

Patel, Kelan; Dunstan, Thomas D.; Nishino, Takafumi

doi:10.3390/en14196437

Cited by 10 publications

(30 citation statements)

References 20 publications

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“…However, this is valid for our simplified analysis where the flow across the farm is mostly fully developed and is driven purely by a PGF. As noted earlier, it was found by Patel et al (2021) that M can be well approximated by M = 1 + ζ(1 − β) and ζ was typically between 5 and 25 for an offshore wind farm site. Substituting this expression for M into (4.5) gives…”

Section: Prediction Of Wind Farm Performancementioning

confidence: 59%

“…without resolving individual turbines. Patel et al (2021) used such an NWP model to demonstrate that, for most cases, M varied almost linearly with β (for a realistic range of β between 1 and 0.8). Therefore, M can be approximated by…”

Section: Two-scale Momentum Theorymentioning

confidence: 99%

“…β = 1. Preliminary results of an extended study from Patel et al (2021) show that ζ changes according to atmospheric conditions and decreases exponentially with increasing farm size (see Appendix B). Although the details of how ζ changes with weather conditions are still unclear and need to be clarified in future studies, in the present study, we take 0 < ζ < 25 as a typical range of the wind extractability for large offshore wind farms.…”

Section: Two-scale Momentum Theorymentioning

confidence: 99%

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Two-scale interaction of wake and blockage effects in large wind farms

2022

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Turbine wake and farm blockage effects may significantly impact the power produced by large wind farms. In this study, we perform large-eddy simulations (LES) of 50 infinitely large offshore wind farms with different turbine layouts and wind directions. The LES results are combined with the two-scale momentum theory (Nishino & Dunstan, J. Fluid Mech., vol. 894, 2020, p. A2) to investigate the aerodynamic performance of large but finite-sized farms as well. The power of infinitely large farms is found to be a strong function of the array density, whereas the power of large finite-sized farms depends on both the array density and turbine layout. An analytical model derived from the two-scale momentum theory predicts the impact of array density very well for all 50 farms investigated and can therefore be used as an upper limit to farm performance. We also propose a new method to quantify turbine-scale losses (due to turbine–wake interactions) and farm-scale losses (due to the reduction of farm-average wind speed). They both depend on the strength of atmospheric response to the farm, and our results suggest that, for large offshore wind farms, the farm-scale losses are typically more than twice as large as the turbine-scale losses. This is found to be due to a two-scale interaction between turbine wake and farm induction effects, explaining why the impact of turbine layout on farm power varies with the strength of atmospheric response.

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Section: Prediction Of Wind Farm Performancementioning

confidence: 59%

Section: Two-scale Momentum Theorymentioning

confidence: 99%

Section: Two-scale Momentum Theorymentioning

confidence: 99%

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Two-scale interaction of wake and blockage effects in large wind farms

2022

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“…Here ζ is the momentum response parameter for the atmosphere, which represents the ability of the atmosphere to sustain wind speeds against the resistance caused by the wind farm. Typical values of which are expected to be between 5 and 25 for a realistic offshore wind farm [8]. As shown in figure 3 as we decrease the lateral turbine spacing the global power coefficient C p falls for all values of ζ between 5 and 25.…”

Section: Wind-farm Blockage Vs Local Blockagementioning

confidence: 90%

A data-informed analytic model for turbine power prediction with anisotropic local blockage effects

Juniper

Nishino²

2022

J. Phys.: Conf. Ser.

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This paper presents a new analytic approach for estimating the local power coefficient of a turbine experiencing anisotropic local blockage effects. Data-driven methods are employed first to approximately obtain a known analytic expression for isotropic local blockage effects, and then deployed to find candidate expressions for anisotropic local blockage effects. The dataset for the analysis of anisotropic local blockage is collected from 3D Reynolds-averaged Navier-Stokes (RANS) simulations of an infinitely wide array of actuator disks for nearly 2,000 different blockage configurations. This study builds upon previous work in array optimisation of both tidal and wind turbines, where the local power coefficient may increase substantially for optimal array configuration. A brief discussion on the relationship between the local blockage and wind farm blockage is also provided. Other theoretical approaches and possible refinements to the presented analytic model are also discussed.

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“…This was based on the assumption that, for an infinitely large wind farm, the driving force of the wind is not affected by the existence of wind turbines [1,22]. In reality, the driving force of wind over a large (finite-size) wind farm should depend on the characteristics of mesoscale atmospheric response [29,30]. To obtain the correct driving force and, thus, the correct wind speed for a real wind farm, we would need to assess the 'extractability' of wind at a given wind farm site using a mesoscale weather model [30], but this is outside the scope of the present study.…”

Section: Rans Setupmentioning

confidence: 99%

Blade-Resolved CFD Simulations of a Periodic Array of NREL 5 MW Rotors with and without Towers

Lian-xiang

Delafin

Tsoutsanis

et al. 2022

Wind

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A fully resolved (FR) NREL 5 MW turbine model is employed in two unsteady Reynolds-averaged Navier–Stokes (URANS) simulations (one with and one without the turbine tower) of a periodic atmospheric boundary layer (ABL) to study the performance of an infinitely large wind farm. The results show that the power reduction due to the tower drag is about 5% under the assumption that the driving force of the ABL is unchanged. Two additional simulations using an actuator disc (AD) model are also conducted. The AD and FR results show nearly identical tower-induced reductions of the wind speed above the wind farm, supporting the argument that the AD model is sufficient to predict the wind farm blockage effect. We also investigate the feasibility of performing delayed-detached-eddy simulations (DDES) using the same FR turbine model and periodic domain setup. The results show complex turbulent flow characteristics within the farm, such as the interaction of large-scale hairpin-like vortices with smaller-scale blade-tip vortices. The computational cost of the DDES required for a given number of rotor revolutions is found to be similar to the corresponding URANS simulation, but the sampling period required to obtain meaningful time-averaged results seems much longer due to the existence of long-timescale fluctuations.

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Time-Dependent Upper Limits to the Performance of Large Wind Farms Due to Mesoscale Atmospheric Response

Cited by 10 publications

References 20 publications

Two-scale interaction of wake and blockage effects in large wind farms

Two-scale interaction of wake and blockage effects in large wind farms

A data-informed analytic model for turbine power prediction with anisotropic local blockage effects

Blade-Resolved CFD Simulations of a Periodic Array of NREL 5 MW Rotors with and without Towers

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