Design of Risk Mitigation Strategies for Wind Farms Using Detached-Eddy Simulation with Turbulent Inflow

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1 Design of Risk Mitigation Strategies for Wind Farms Using Detached-Eddy Simulation with Turbulent Inflow Yavor Hrsitov Vestas Power Solutions, DK

2 VestasFOAM- CFD platform for siting and new concept development A fully integrated OpenFOAM-based CFD package developed by Vestas CFD group. Interfaces designed for streamlined and automated procedures including pre- and postprocessing. 2 Vindkraftnet, June 01, 2017

3 Wind speed Accuracy vs. Cost Time Steady RANS (Level 1/2) Unsteady RANS (Level 2.5) Hybrid RANS-LES /Detached-Eddy Simulation (DES) (Level 3) Accuracy Cost 3 Large-Eddy Simulation (LES) (Level 4/5) Direct Numerical Simulation (DNS) Vindkraftnet, June 01, 2017

4 Why DES? A combination of RANS and LES to compromise between accuracy and cost. Start from a basic RANS model (e.g. k-ε, k-ω, Spalart-Allmaras, etc.); Estimate the turbulence length scale (eddy size) l T as a function of turbulence variables (e.g. l T ~ k 1/2 /ω for the k-ω RANS model). If l T < Δ, eddies cannot be resolved with the current mesh: remain as RANS. If l T > Δ, eddies can be resolved with the current mesh: switch to LES. ᅳ Increase the dissipation; ᅳ Reduce TKE; ᅳ Reduce the eddy viscosity. RANS mode LES mode k-ω SST-based DES model by Menter et al. (2003) was chosen in order to maintain the analogy with twoequation RANS models (e.g. for direct term-by-term comparisons with our RANS CFD results): In-house OpenFOAM class komegasstdes was created by converting the RANS class komegasst. 4 Vindkraftnet, June 01, 2017

5 Z Level 3 (DES) set-up and report with results X 5 Vindkraftnet, June 01, 2017

6 Mann turbulent inflow vs. Log low inflow Log Low inflow Mann turbulent inflow 6 Vindkraftnet, June 01, 2017

7 Probability-density distributions of wind speed and wind direction 7 Vindkraftnet, June 01, 2017

8 Probability-density risk analysis for extreme wind conditions P P V 5% V m % P 5% P P V P DES DES DES V ( V ) d V, ( ) d, ( ) d. V m : mean velocity difference; V : sdv velocity difference; : sdv direction difference. (from the IEC standard Gaussian curve) WTG09, sector 270 WTG16, sector 060 WTG14, sector 210 V P 45.4%!!! P 33.8%!!! 5% 5% P 5% 25.1%!!! 8 Vindkraftnet, June 01, 2017

9 Probability-density risk analysis for extreme wind conditions 9 Vindkraftnet, June 01, 2017

10 GenSpd WindHub Wind Speed diff. [m/s] Validation case 1 SmartScaling: 0.01*Sys *Sys *Sys *Sys Negative wind shear measured at # Time [s] Max.= ; Min.= Avg.= ; Std.= Time [s] Max.=32.70; Min.=5.20 Avg.=20.94 m/s; 'Turb.Int.=19 % Vindkraftnet, June 01, 2017 #19353 V80; SW-rel:20764; C:\VMP\19353\vdf\ VDF; 2005-Sep-29 14:56: Sep-29 17:36:32 ( [s]) Max.=12.80; Min.= JP: VDAT Dec :20:03 Avg.=-3.56; Std.=4.66 *VDif f * WindHub Sy s413 GenSpd GenSpdRf WTG WTG WTG WTG WTG WTG WTG WTG WTG WTG WTG WTG WTG WTG WTG19343 name sector sector2700 sector WTG19359 WTG WTG19365 WTG WTG19351 WTG WTG19344 WTG WTG19346 WTG WTG19354 WTG WTG19352 WTG WTG19356 WTG WTG19350 WTG WTG19349 WTG WTG19369 WTG WTG WTG WTG WTG WTG WTG WTG WTG WTG WTG WTG WTG WTG WTG Results for sector 240 for #19353 show probability for negative wind shear outside IEC norm which is in line with the Negative wind shear report.

11 D1% *VDiff*Avg *VDiff*Avg0.3sAvg WindHubStdNorm Sys325StdNorm Validation case sec. statistics from turbine #6134 (V47) Data: C:\MatlabApp\VdatOut\Stat\6134\600s (1782 points in 35 files) 45 WindHubStdNorm Sy s325stdnorm -5-5 Results for sector 000 for WTG15 ( PS3.A #6134 ) show MAT: 61.8 % negative wind PS3.B sec shear outside IEC norm which is in line 10 with 15 the 20 Negative wind shear WindHubAvg WindHubAvg report. Negative 30 wind shear measured at WTG ( #6134) Vindkraftnet, June 01, WindHubAvg *VDif f *Av g *VDif f *Min *VDif f *Max *VDif f *Av g0.3scd1% Sys325Avg WTG name sector330 sector000 *VDif f *Av g0.3sav g WTG15 *VDif f *Av g0.3smin *VDif f *Av g0.3smax WTG WTG APMGridAv g APMGridMax APMGridMin

12 Validation case 3 12 Vindkraftnet, June 01, 2017

13 Validation case Vindkraftnet, June 01, 2017

14 70 deg Sector DES WTG07 14 Vindkraftnet, June 01, 2017

15 High-fidelity CFD simulation of forest benefits A more thorough understanding of underlying flow physics including turbulence structure evolution: (Brown & Roshko 1974) (Finnigan 2000) (Large-eddy simulation by Finnigan et al. 2009) 15 Vindkraftnet, June 01, 2017

16 Sanz (2003) forest model for k-ε RANS simulation Dk Dt = P ε + P C D C P C = LAD C D β P U 3 D C = LAD C D β D Uk Dε Dt = C 1P C 2 ε T 2 β D = C μ a + C 3 P c D c T 2 3 βp + 3 σ k 2 C 3 = σ k σ ε (a = 0.05) C μ 6 2 a 2 3 C2 C 1 16 Vindkraftnet, June 01, 2017

17 CFD forest model for RANS simulation Source terms added within the forest: Du Dt = LAD C D u u FLOW 17 Vindkraftnet, June 01, 2017

18 Validation case- DES with forest WTG % of Max # alarms DES with forest: negative shear DES without forest: negative shear % 14.59% 13.21% % 37.82% 32.10% % 35.01% 25.30% % 1.07% 0.11% % 12.45% 1.31% % 4.76% 0.35% % 11.97% 2.24% % 97.20% 29.20% % 2.45% 0.00% % 0.00% 0.00% % 7.59% 1.50% % 0.00% 0.00% % 0.00% 0.00% % 2.19% 2.90% % 12.16% 2.69% % 3.20% 2.32% % 0.00% 0.00% % 0.00% 0.00% % 11.81% 4.41% % 0.00% 0.00% % 9.38% 3.69% % 61.09% 2.30% % 20.13% 20.90% Data for alarms in sector from -005 to +005 for 7 years. Only the 000 sector was simulated with DES. Results showing reasonable improvement with the forest model activated are marked in blue. Alarms can be triggered by non-flow related (mechanical) reasons as well 18 Vindkraftnet, June 01, 2017

19 Discussion 1. Mesh resolution ( horizontal, vertical) 2. Turbulent inflow conditions to trigger switch from RANS to LES 3. Tuning F1 and F2 blending functions in the DES formulation for ABL applications Gritskevich et al, Flow Turbulence Combust (2012) 88: ,DOI /s Forest with DES- further validation 19 Vindkraftnet, June 01, 2017

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