The consideration of atmospheric stability within wind farm AEP calculations

Schmidt, Jonas; Chang, Chi-Yao; Dörenkämper, Martin; Salimi, Milad; Teichmann, Tim; Stoevesandt, Bernhard

doi:10.1088/1742-6596/749/1/012002

Cited by 9 publications

(7 citation statements)

References 8 publications

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“…For the benchmark, engineering wake model simulations were run for over 80000 states of input conditions by three external modellers. In addition, three simulations with the Jensen model [7] from the OpenSource code FOXES [8] were added. The models and their specifics are listed in Table 1 and further described in the following.…”

Section: Model Input and Model Descriptionsmentioning

confidence: 99%

Benchmarking engineering wake models for farm-to-farm interactions

Vollmer,

Wurps,

Dörenkämper

2024

J. Phys.: Conf. Ser.

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Inter-farm wakes between offshore wind farms can cause a significant production loss at the downstream wind farm. We compare the power production at two wind farms that are separated by approximately 20 km to engineering model results provided by three different wind farm developers. Model inflow conditions were derived from the nacelle anemometry of the wake-creating wind farm and a mesoscale simulation. The comparison reveals that the model results show in general a good approximation of the wake losses, but underestimate the increase of losses in stable stability conditions. Here, specifically the measured wakes appear to be much wider than the modelled wakes.

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Section: Model Input and Model Descriptionsmentioning

confidence: 99%

Benchmarking engineering wake models for farm-to-farm interactions

Vollmer,

Wurps,

Dörenkämper

2024

J. Phys.: Conf. Ser.

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“…The engineering model employed in this work is the Farm Optimization and eXtended yield Evaluation Software (FOXES, [12]). It can directly use WRF data as input, for which fourdimensional (time, x, y, z) fields were extracted every 10 minutes.…”

Section: Engineering Modelmentioning

confidence: 99%

Multi-model approach for wind resource assessment

Sengers,

Vollmer,

Dörenkämper

2024

J. Phys.: Conf. Ser.

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This study presents a multi-model approach for wind resource assessment of a wind farm affected by external wakes. The Weather Research and Forecasting model (WRF), a mesoscale model, is employed to simulate external wind farm wakes, while the Farm Optimization and eXtended yield Evaluation Software (FOXES), an engineering model, is used to simulate the wind farm of interest. This hybrid approach addresses the limitation of both models, mainly the lack of layout effects in mesoscale models and the poor representation of cluster wakes in engineering models. A case study, focusing on the Kaskasi wind farm in the Heligoland cluster, shows that the WRF model predicts larger wake losses compared to FOXES, with the multi-model approach yielding intermediate results. Systematic differences are found as a function of wind speed and seasonality, while the models behave differently as a function of turbulence intensity. The external wake effect was clearly identified for one wind direction sector in WRF and the multi-model approach, while FOXES failed to represent this. The proposed methodology does not only enhance classic resource assessment, but also facilitates efficient layout optimization using cluster waked inflow and allows for wind farm control studies, contributing to both planning and operational phases of wind farm management.

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“…Despite the fact that the IEC standard (IEC61400-1 (ED4) 2019, 2019) specifies a power law vertical model independent of atmospheric stability to perform load calculations, the dependence of this and, in turn, the turbulence intensity with atmospheric stability is widely demonstrated (Emeis, 2013;Lange et al, 2004b;Peña and Hahmann, 2012). In addition several stud-ies have demonstrated the impact of atmospheric stability on wind resource assessment (Lange et al, 2004a), wind turbine power curves and annual energy production (AEP) calculations (Martin et al, 2016;Schmidt et al, 2016); wind turbine loads (Kelly et al, 2014;Sathe et al, 2013) and wind turbine wakes (Abkar and Porté-Agel, 2015;Hansen et al, 2010;Machefaux et al, 2016). This is why the wind industry is developing models and methods to include the effect of atmospheric stability in the layout design and energy yield assessment.…”

Section: Introductionmentioning

confidence: 99%

On the measurement of stability parameter over complex mountainous terrain

et al. 2022

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Abstract. Atmospheric stability has a significant effect on wind shear and turbulence intensity, and these variables, in turn, have a direct impact on wind power production and loads on wind turbines. It is therefore important to know how to characterise atmospheric stability in order to make better energy yield estimation in a wind farm. Based on the research-grade meteorological mast at Alaiz (CENER's test site in Navarre, Spain) named MP5, this work compares and evaluates different instrument set-ups and methodologies for stability characterisation, namely the Obukhov parameter, measured with a sonic anemometer, and the bulk Richardson number based on two temperature and one wind speed measurement. The methods are examined considering their theoretical background, implementation complexity, instrumentation requirements, and practical use in connection to wind energy applications. The sonic method provides a more precise local measurement of stability while the bulk Richardson is a simpler, robust and cost-effective technique to implement in wind assessment campaigns. Using the sonic method as a benchmark, it is shown that to obtain reliable bulk Richardson measurements in onshore sites it is necessary to install one of the temperature sensors close to the ground where the temperature gradient is stronger.

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The consideration of atmospheric stability within wind farm AEP calculations

Cited by 9 publications

References 8 publications

Benchmarking engineering wake models for farm-to-farm interactions

Benchmarking engineering wake models for farm-to-farm interactions

Multi-model approach for wind resource assessment

On the measurement of stability parameter over complex mountainous terrain

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