A new wake‐merging method for wind‐farm power prediction in the presence of heterogeneous background velocity fields

Lanzilao, Luca; Meyers, Johan

doi:10.1002/we.2669

Cited by 42 publications

(38 citation statements)

References 52 publications

(141 reference statements)

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“…where u i | (x,y) is the contribution of the wake of each turbine i at the downstream location (x, y) (Machefaux et al 2015). Alternative superposition methods include summing the square of the velocity deficits (Katic et al 1987) as well as the more recent work by Lanzilao and Meyers (2021) which takes into account the heterogeneity of the background velocity field.…”

Section: Analytical Wake Modelling Using Florismentioning

confidence: 99%

Combining shallow-water and analytical wake models for tidal array micro-siting

Jordan

Dundovic

Fragkou

et al. 2022

J. Ocean Eng. Mar. Energy

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For tidal-stream energy to become a competitive renewable energy source, clustering multiple turbines into arrays is paramount. Array optimisation is thus critical for achieving maximum power performance and reducing cost of energy. However, ascertaining an optimal array layout is a complex problem, subject to specific site hydrodynamics and multiple inter-disciplinary constraints. In this work, we present a novel optimisation approach that combines an analytical-based wake model, FLORIS, with an ocean model, Thetis. The approach is demonstrated through applications of increasing complexity. By utilising the method of analytical wake superposition, the addition or alteration of turbine position does not require re-calculation of the entire flow field, thus allowing the use of simple heuristic techniques to perform optimisation at a fraction of the computational cost of more sophisticated methods. Using a custom condition-based placement algorithm, this methodology is applied to the Pentland Firth for arrays with turbines of $$3.05\,\hbox {m}/\hbox {s}$$ 3.05 m / s rated speed, demonstrating practical implications whilst considering the temporal variability of the tide. For a 24-turbine array case, micro-siting using this technique delivered an array 15.8% more productive on average than a staggered layout, despite flow speeds regularly exceeding the rated value. Performance was evaluated through assessment of the optimised layout within the ocean model that treats turbines through a discrete turbine representation. Used iteratively, this methodology could deliver improved array configurations in a manner that accounts for local hydrodynamic effects.

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Section: Analytical Wake Modelling Using Florismentioning

confidence: 99%

Combining shallow-water and analytical wake models for tidal array micro-siting

Jordan

Dundovic

Fragkou

et al. 2022

J. Ocean Eng. Mar. Energy

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“…The choice of a wake superposition method is the last topic to discuss concerning the set-up of the engineering model. As the streamline wake model is meant for dealing with heterogeneous inflow conditions, we decided to consider in addition to the linear superposition method, which is typically advised when accounting for wake-added turbulence intensity (Niayifar and Porté-Agel, 2015), also the novel wake superposition method presented by Lanzilao and Meyers (2020). The purpose of this new method is, in fact, to cope better with non-homogeneous wind fields.…”

Section: Study-specific Set-upmentioning

confidence: 99%

“…Additionally, to avoid a negative velocity to be computed in velocity fields with large wind speed gradients the wake deficit is limited to not overcome the local background wind speed at the point x. The second superposition method considered is the one described in Lanzilao and Meyers (2020):…”

Section: Study-specific Set-upmentioning

confidence: 99%

“…The recently published approach by Lanzilao and Meyers (2022) applies a methodology for deflecting the turbine wakes along the streamlines from a heterogeneous background flow field. In this study, we suggest the coupling of engineering wake models with mesoscale background wind fields for taking into account mesoscale wind direction changes and thus apply an approach similar to Lanzilao and Meyers (2022) but on larger scales. This allows us to demonstrate how the method works and to discuss its implications when simulating for AEP calculation or site assessment.…”

Section: Introductionmentioning

confidence: 99%

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An investigation of mesoscale wind direction changes and their consideration in engineering models

Brandis

Centurelli

Schmidt

et al. 2022

Preprint

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Abstract. We propose that considering mesoscale wind direction changes in the computation of wind farm cluster wakes could reduce the uncertainty of engineering wake modelling tools. The relevance of mesoscale wind direction changes is investigated using a wind climatology of the German Bight area covering 30 years, derived from the New European Wind Atlas (NEWA). Furthermore, we present a new solution for engineering modelling tools that accounts for the effect of such changes on the propagation of cluster wakes. Mesoscale wind direction changes are found to exceed 7° per 100 km in 50 % of all cases and are particularly large in the lower partial load range, which is associated with strong wake formation. Here, the quartiles reach up to 20° per 100 km. Especially on a horizontal scale of several tens to a hundred kilometers, wind direction changes are relevant. Both the temporal and spatial scale at which large wind direction changes occur depend on the presence of pressure systems. Furthermore, atmospheric conditions which promote far-reaching wakes were found to align with a strong turning in 14.6 % of the cases. In order to capture these mesoscale wind direction changes in engineering model tools, a wake propagation model was implemented into the Fraunhofer IWES wind farm and wake modelling software flappy. The propagation model derives streamlines from the horizontal velocity field and forces the single turbine wakes along these streamlines. This model has been qualitatively evaluated by simulating the flow around wind farm clusters in the German Bight with data from the mesoscale atlas of NEWA and comparing the results to Synthetic Aperture Radar (SAR) measurements for selected situations. The comparison reveals that the flow patterns are in good agreement if the underlying mesoscale data capture the velocity field well. For such cases, the new model provides an improvement compared to the baseline approach of engineering models, which assumes a straight-line propagation of wakes. The streamline and the baseline model have been further compared in terms of their quantitative effect on the energy yield. Simulating two neighbouring wind farm clusters over a time period of 10 years, it is found that there are no significant differences across the models when computing the total energy yield of both clusters. However, extracting the wake effect of one cluster on the other, the two models show a difference of about 1 %. Even greater differences are commonly observed when comparing single situations. Therefore, we claim that the model has the potential to reduce uncertainty in applications such as site assessment and short-term power forecasting.

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“…Lanzilao and Meyers (2021b)). In the future, we foresee further improvements of the TLM, among others, including hydrodynamic effects in the boundary layer, and upgrading the wake model to include the improved wake merging model by Lanzilao and Meyers (2021a). Next to that, we plan further validation against detailed large-eddy simulations (similar to Allaerts and Meyers (2019)), and data from operational wind farms.…”

mentioning

confidence: 99%

Extending the applicability of a wind-farm gravity-wave model to vertically non-uniform atmospheres

Devesse

Lanzilao

Jamaer

et al. 2022

Preprint

Self Cite

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Abstract. Recent research suggests that atmospheric gravity waves can affect off-shore wind farm performance. A fast wind-farm boundary-layer model has been proposed to simulate the effects of these gravity waves on wind-farm operation by Allaerts and Meyers (2019). The current work extends the applicability of that model to free atmospheres in which wind and stability vary with altitude. We validate the model using reference cases from literature on mountain waves. Analysis of two reference flows shows that internal gravity wave resonance caused by the atmospheric non-uniformity can prohibit perturbations in the ABL at the wavelengths where it occurs. To determine the overall impact of the vertical variations in the atmospheric conditions on wind farm operation, we consider one year of operation of the Belgian–Dutch wind-farm cluster with the extended model. We find that this impact on individual flow cases is often of the same order of magnitude as the total flow perturbation. In 16.5 % of the analysed flows, the relative difference in upstream velocity reduction between uniform and non-uniform free atmospheres is more than 30 %. However, this impact is small when averaged over all cases. This suggests that variations in the atmospheric conditions should be taken into account when simulating wind-farm operation in specific atmospheric conditions.

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A new wake‐merging method for wind‐farm power prediction in the presence of heterogeneous background velocity fields

Cited by 42 publications

References 52 publications

Combining shallow-water and analytical wake models for tidal array micro-siting

Combining shallow-water and analytical wake models for tidal array micro-siting

An investigation of mesoscale wind direction changes and their consideration in engineering models

Extending the applicability of a wind-farm gravity-wave model to vertically non-uniform atmospheres

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