Data analysis and simulation of the Lillgrund wind farm

Sebastiani, Alessandro; Castellani, Francesco; Crasto, Giorgio; Segalini, Antonio

doi:10.1002/we.2594

Cited by 40 publications

(35 citation statements)

References 21 publications

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“…The reference velocity U ref is the velocity of the first row when all successive rows are placed 32D downstream. Sebastiani et al [106] evaluated blockage effects in the Nysted wind farm using field measurements and found the effect to be about 2%, which is consistent with the above formula. They also assessed blockage using WindSim, OpenFOAM, and ORFEUS and, depending on the model and wind direction, the estimated effect is between 2 ´4%.…”

Section: Introductionsupporting

confidence: 63%

Modelling wakes and blockage i large-scale wind farms

Strickland¹

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Section: Introductionsupporting

confidence: 63%

Modelling wakes and blockage i large-scale wind farms

Strickland¹

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“…The Lillgrund offshore wind farm is located approximately 10 km off the coast of southern Sweden, just south of the Öresund Bridge, where average wind speeds are overall close to 8.5 m s −1 (Sebastiani et al, 2021). The wind farm contains 48 wind turbines (Siemens SWT-2.3-93) with a total capacity of 110 megawatts (MW).…”

Section: Introductionmentioning

confidence: 99%

Comparison of Large Eddy Simulations against measurements from the Lillgrund offshore wind farm

Sood

Simon

Vitsas

et al. 2022

Preprint

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Abstract. Numerical simulation tools such as Large Eddy Simulations (LES) have been extensively used in recent years to simulate and analyze turbine-wake interactions within large wind farms. However, to ensure the reliability of the performance and accuracy of such numerical solvers, validation against field measurements is essential. To this end, a measurement campaign is carried out at the Lillgrund offshore wind farm to gather data for the validation of an in-house LES solver. Flow field data is collected from the farm using three long-range WindScanners, along with turbine performance and load measurements from individual turbines. Turbulent inflow conditions are reconstructed from an existing precursor database using a scaling-and-shifting approach, proposed so that the generated inflow statistics match the measurements. Thus, 5 different simulation cases are setup, corresponding to 5 different inflow conditions at the Lillgrund wind farm. Operation of the 48 Siemens 2.3 MW turbines from the Lillgrund wind farm is parameterized in the flow domain using an Aeroelastic Actuator Sector Model (AASM). Time-series turbine performance metrics from the simulated cases are compared against field measurements to evaluate the accuracy of the optimization framework, turbine model and flow solver. In general, results from the numerical solver show good comparison in terms of power production, turbine loading and wake recovery. Nevertheless, larger errors for a few turbines in the wind farm across the simulated cases reveal the need for an improved controller implementation, and possibly a finer simulation grid for capturing wake turbulence.

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“…More recently, the wind energy science community has recognized the importance of the pressure field associated with the rotor thrust force, which can modify the incoming atmospheric boundary layer (ABL), specifically reducing the rotor equivalent velocity, and leading to small yet noticeable under-performance in terms of power capture. This physical process has been typically dubbed as wind farm blockage, as documented through numerical simulations [5], yet a few field campaigns were performed for its characterization [6,7].…”

Section: Introductionmentioning

confidence: 99%

“…Understanding pressure-induced effects on wind farm performance is also important in light of the local speed enhancement for turbine arrays, as reported in theoretical [8], numerical [9,10], and wind tunnel studies [11] , which clashed with the power losses observed for real wind farms [6,11]. Further, the role of atmospheric stratification on rotor-induced effects of the incoming wind is still not clearly understood, yet recent studies showed more severe flow modifications occurring under stable atmospheric conditions as a consequence of the vertical flow confinement due to a smaller boundary layer height and gravity waves [12,13].…”

Section: Introductionmentioning

confidence: 99%

Effects of the thrust force induced by wind turbine rotors on the incoming wind field: A wind LiDAR experiment

Letizia

Moss

Puccioni

et al. 2022

J. Phys.: Conf. Ser.

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A field experiment was conducted to investigate the effects of the thrust force induced by utility-scale wind turbines on the incoming wind field. Five wind profiling LiDARs and a scanning Doppler pulsed wind LiDAR were deployed in the proximity of a row of four wind turbines located over relatively flat terrain, both before and after the construction of the wind farm. The analysis of the LiDAR data collected during the pre-construction phase enables quantifying the wind map of the site, which is then leveraged to correct the post-construction LiDAR data and isolate rotor-induced effects on the incoming wind field. The analysis of the profiling LiDAR data allows for the identification of the induction zone upstream of the turbine rotors, with an increasing velocity deficit moving from the top tip towards the bottom tip of the rotor. The largest wind speed reduction (about 5%) is observed for convective conditions and incoming hub-height wind speed between cut-in and rated wind speeds. The scanning LiDAR data indicate the presence of speedup regions within the gaps between adjacent turbine rotors. Speedup increases with reducing the transverse distance between the rotors, atmospheric instability (maximum 15%), while a longer streamwise extent of the speedup region is observed under stable atmospheric conditions.

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Data analysis and simulation of the Lillgrund wind farm

Cited by 40 publications

References 21 publications

Modelling wakes and blockage i large-scale wind farms

Modelling wakes and blockage i large-scale wind farms

Comparison of Large Eddy Simulations against measurements from the Lillgrund offshore wind farm

Effects of the thrust force induced by wind turbine rotors on the incoming wind field: A wind LiDAR experiment

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