LES* IS MORE! * L ARGE E DDY S IMULATIONS BY VORTEX. WindEnergy Hamburg 2016
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1 LES* IS MORE! * L ARGE E DDY S IMULATIONS BY VORTEX WindEnergy Hamburg 2016
2 OUTLINE MOTIVATION Pep Moreno. CEO, BASIS Alex Montornés. Modelling Specialist, VALIDATION Mark Žagar. Modelling Specialist, Vestas Q & A LES IS MORE!
3 Time series, why? LES IS MORE!
4 Time series, why? State-of-the-art resource analysis is based on distributions LES IS MORE!
5 Time series, why? If full time series were available, you could discriminate (day/night) LES IS MORE!
6 Time series, why? If full time series were available, you could cross-relate variables (TI vs. shear) LES IS MORE!
7 Time series, why? If full time series were available, you could analyse extreme events (ramps) LES IS MORE!
8 The advantages of measured time series compared to distributions are true What is not true is that the showed examples were measurements! LES IS MORE!
9 Have you ever wished to have a time series of measurements at each turbine position of your planned or existing wind farm? Large Eddy Simulations (LES) produces something outstandingly similar! LES IS MORE!
10 Guess which are the measurements and which are the model results LES IS MORE!
11 Measured time series are scarce (expensive) Distributions come mainly from windfield extrapolation (modeling): WAsP, CFD LES delivers probably the most measurementlike set of synthetic time series that atmospheric modeling can achieve today LES IS MORE!
12 LES IS MORE! LES produces real (physical) 10 averages LES IS MORE!
13 LES IS MORE! LES produces 3 samples (TI, gust ) LES IS MORE!
14 LES IS MORE! LES produces 3D results (shear and veer) LES IS MORE!
15 LES: -Powered by NCAR's cutting-edge WRF-LES model -Deliverables: 1 full-year, 10' averages, 3'' standard deviation (speed & direction) and gust (speed) -All heights included for shear and veer calculation -Available anywhere; no measurements needed -Validated at 100+ sites -Delivered in 5-6 days LES IS MORE!
16 -LES: A new horizon in wind resource WRF LES coming to age info@vortexfdc.com LES in wind resource assessment applications
17 -LES: A new horizon in wind resource info@vortexfdc.com LES in wind resource assessment applications
18 -LES: A new horizon in wind resource Characteristic time info@vortexfdc.com LES in wind resource assessment applications Characteristic length
19 -LES: A new horizon in wind resource 1000 Years 100 Years 10 Years 1 Year Characteristic time 1 Month 1 week 1 day 1 h 10 min 1 min 10 s 1 s <0.1 s 10 cm 1 cm <1 mm 1 m km km km 100 km 10 km 1 km 100 m 10 m info@vortexfdc.com LES in wind resource assessment applications Characteristic length
20 -LES: A new horizon in wind resource 1000 Years Fluid dynamics Meteorology Climate Characteristic time 100 Years 10 Years 1 Year 1 Month 1 week 1 day 1 h 10 min 1 min Climate variations ENSO Seasonal Planetary waves Synoptic scale Mesoscale Microscale 10 s 1 s <0.1 s 10 cm 1 cm <1 mm Molecular diffusion 1 m km km km 100 km 10 km 1 km 100 m 10 m Small eddies info@vortexfdc.com LES in wind resource assessment applications Characteristic length
21 -LES: A new horizon in wind resource 1000 Years Fluid dynamics Meteorology Climate Characteristic time 100 Years 10 Years 1 Year 1 Month 1 week 1 day 1 h 10 min 1 min Climate variations ENSO Seasonal Planetary waves Synoptic scale Mesoscale Microscale 10 s 1 s <0.1 s 10 cm 1 cm <1 mm Molecular diffusion 1 m km km km 100 km 10 km 1 km 100 m 10 m Small eddies info@vortexfdc.com LES in wind resource assessment applications Characteristic length
22 -LES: A new horizon in wind resource 1000 Years Fluid dynamics Meteorology Climate 100 Years 10 Years Wind industry interest Climate variations Characteristic time 1 Year 1 Month 1 week 1 day 1 h 10 min 1 min ENSO Seasonal Planetary waves Synoptic scale Mesoscale Microscale 10 s 1 s <0.1 s 10 cm 1 cm <1 mm Molecular diffusion 1 m km km km 100 km 10 km 1 km 100 m 10 m Small eddies info@vortexfdc.com LES in wind resource assessment applications Characteristic length
23 -LES: A new horizon in wind resource 1000 Years 100 Years 10 Years Fluid dynamics Wind industry interest Meteorology Climate Climate models Climate variations Characteristic time 1 Year 1 Month 1 week 1 day 1 h 10 min 1 min ENSO Seasonal Global Planetary waves models Synoptic scale Mesoscale Microscale 10 s 1 s <0.1 s 10 cm 1 cm <1 mm Molecular diffusion 1 m km km km 100 km 10 km 1 km 100 m 10 m Small eddies info@vortexfdc.com LES in wind resource assessment applications Characteristic length
24 -LES: A new horizon in wind resource 1000 Years 100 Years 10 Years Fluid dynamics Wind industry interest Meteorology Climate Climate models Climate variations Characteristic time 1 Year 1 Month 1 week 1 day 1 h 10 min 1 min Mesoscale models ENSO Seasonal Global Planetary waves models Synoptic scale Mesoscale Microscale 10 s 1 s <0.1 s 10 cm 1 cm <1 mm Molecular diffusion 1 m km km km 100 km 10 km 1 km 100 m 10 m Small eddies info@vortexfdc.com LES in wind resource assessment applications Characteristic length
25 -LES: A new horizon in wind resource 1000 Years 100 Years 10 Years Fluid dynamics Wind industry interest Meteorology Climate Climate models Climate variations Characteristic time 1 Year 1 Month 1 week 1 day 1 h 10 min 1 min CFD models Mesoscale models ENSO Seasonal Global Planetary waves models Synoptic scale Mesoscale Microscale 10 s 1 s <0.1 s 10 cm 1 cm <1 mm Molecular diffusion 1 m km km km 100 km 10 km 1 km 100 m 10 m Small eddies info@vortexfdc.com LES in wind resource assessment applications Characteristic length
26 -LES: A new horizon in wind resource Large eddies Small eddies Input energy Dissipation Energy flux info@vortexfdc.com LES in wind resource assessment applications
27 -LES: A new horizon in wind resource Large eddies Small eddies RANS Resolved Modeled Average info@vortexfdc.com LES in wind resource assessment applications
28 -LES: A new horizon in wind resource Large eddies Small eddies RANS Avg. LES Resolved Dynamic Modeled info@vortexfdc.com LES in wind resource assessment applications
29 -LES: A new horizon in wind resource Large eddies Small eddies RANS LES Avg. Dyn. DNS Resolved Dynamic info@vortexfdc.com LES in wind resource assessment applications
30 -LES: A new horizon in wind resource DNS LES RANS Dyn. Dyn. Avg. Adapted from Maries, A., Haque, M. A., Yilmaz, S. L., Nik, M. B., Marai, G. E.: New Developments in the Visualization and Processing of Tensor Fields, Springer, pp , D. Laidlaw, A. Villanova info@vortexfdc.com LES in wind resource assessment applications
31 -LES: A new horizon in wind resource DNS LES RANS Dyn. Seconds Dyn. Minutes Avg. Distributions Different tools for different applications info@vortexfdc.com LES in wind resource assessment applications
32 -LES: A new horizon in wind resource 1000 Years 100 Years 10 Years Fluid dynamics Wind industry interest Meteorology Climate Climate models Climate variations Characteristic time 1 Year 1 Month 1 week 1 day 1 h 10 min 1 min CFD models Mesoscale models ENSO Seasonal Global Planetary waves models Synoptic scale Mesoscale Microscale 10 s 1 s <0.1 s 10 cm 1 cm <1 mm Molecular diffusion 1 m km km km 100 km 10 km 1 km 100 m 10 m Small eddies info@vortexfdc.com LES in wind resource assessment applications Characteristic length
33 -LES: A new horizon in wind resource 1000 Years 100 Years 10 Years Fluid dynamics Wind industry interest Meteorology Climate Climate models Climate variations Characteristic time 1 Year 1 Month 1 week 1 day 1 h 10 min 1 min Large Eddy SGS Simulation Mesoscale models ENSO Seasonal Global Planetary waves models Synoptic scale Mesoscale Microscale 10 s 1 s <0.1 s 10 cm 1 cm <1 mm Molecular diffusion 1 m km km km 100 km 10 km 1 km 100 m 10 m Small eddies info@vortexfdc.com LES in wind resource assessment applications Characteristic length
34 -LES: A new horizon in wind resource Coupling mesoscale-les: Challenges Lateral boundary conditions Surface layer and Land Surface Model Terra-Incognita info@vortexfdc.com LES in wind resource assessment applications
35 -LES: A new horizon in wind resource 1000 Years 100 Years 10 Years Fluid dynamics Wind industry interest Meteorology Climate Climate models Climate variations Characteristic time 1 Year 1 Month 1 week 1 day 1 h 10 min 1 min Large Eddy SGS Simulation Mesoscale models Terra Incognita ENSO Seasonal Global Planetary waves models Synoptic scale Mesoscale Microscale 10 s 1 s <0.1 s 10 cm 1 cm <1 mm Molecular diffusion 1 m km km km 100 km 10 km 1 km 100 m 10 m Small eddies info@vortexfdc.com LES in wind resource assessment applications Characteristic length
36 -LES: A new horizon in wind resource Coupling mesoscale-les: Challenges Lateral boundary conditions Surface layer and Land Surface Model Terra-Incognita info@vortexfdc.com LES in wind resource assessment applications
37 -LES: A new horizon in wind resource Lateral boundary conditions Microscale LES BC Mesoscale PBL info@vortexfdc.com LES in wind resource assessment applications
38 -LES: A new horizon in wind resource Lateral boundary conditions BC Mesoscale PBL info@vortexfdc.com LES in wind resource assessment applications
39 -LES: A new horizon in wind resource Lateral boundary conditions θ new = θ old + θ' Muñoz Esparza (2014) + in house R+D BC Mesoscale PBL info@vortexfdc.com LES in wind resource assessment applications
40 -LES: A new horizon in wind resource approach Reanalysis WRF LES Mesoscale PBL info@vortexfdc.com LES in wind resource assessment applications
41 -LES: A new horizon in wind resource approach Reanalysis WRF LES Mesoscale PBL Microscale LES 4 Hz output info@vortexfdc.com LES in wind resource assessment applications
42 -LES: A new horizon in wind resource approach Reanalysis WRF LES Mesoscale PBL Microscale LES 4 Hz output LES = Resolved + eddies Subgrid eddies info@vortexfdc.com LES in wind resource assessment applications
43 -LES: A new horizon in wind resource approach flow composer LES = Resolved + eddies Subgrid eddies info@vortexfdc.com LES in wind resource assessment applications
44 -LES: A new horizon in wind resource approach flow composer Physical based model that reconstruct the real flow considering the resolved and subgrid energy LES = Resolved + eddies Subgrid eddies info@vortexfdc.com LES in wind resource assessment applications
45 -LES: A new horizon in wind resource approach Reanalysis WRF LES Mesoscale PBL Microscale LES Postprocessing 4 Hz output 10' averages 10' standard deviation 3'' gust meters above ground Wind speed, Wind direction, Temperature, Pressure, Richardson Number, PBL Fluxes, Wind Veer, Inflow angle,... info@vortexfdc.com LES in wind resource assessment applications
46 -LES: A new horizon in wind resource -LES validation exercise Wind metrics validated for 93 sites Turbulence Intensity validated for 51 sites info@vortexfdc.com LES in wind resource assessment applications
47 -LES: A new horizon in wind resource -LES validation exercise 1e+02 Spectral density [ ] 1e+00 1e 02 1e 05 1e 03 Frequency (Hz) label Real LES 111 m PBL 3 km info@vortexfdc.com LES in wind resource assessment applications
48 -LES: A new horizon in wind resource -LES validation exercise Mesoscale Microscale Spectral density [ ] 1e+02 1e+00 1e 02 1 y 1 m 1 d 3 h Terra Incognita 10 min 1e 05 1e 03 Frequency (Hz) label Real LES 111 m PBL 3 km info@vortexfdc.com LES in wind resource assessment applications
49 -LES: A new horizon in wind resource -LES validation exercise Wind metrics validated for 93 sites Commonly used wind metrics in the industry: MAE Correlation Weibull parameters Average Std Dev MAE (%) A-shape (%) k-shape (%) R 2 10-min R 2 hourly R 2 daily info@vortexfdc.com LES in wind resource assessment applications
50 -LES: A new horizon in wind resource -LES validation exercise TI(%) validated for 51 sites Which metric to use? 1. MAE between TI-model against TI-obs weighted by bin-ocurrence 2. MAE at 15 m/s bin Average Std Dev MAE MAE info@vortexfdc.com LES in wind resource assessment applications
51 -LES: A new horizon in wind resource WRF LES coming to age info@vortexfdc.com LES in wind resource assessment applications
52 Applications and validation of meso-γ and microscale (WRF / WRF-LES) meteorological modeling in wind energy Mark Žagar Specialist, Plant Siting & Forecasting Vestas Technology & Service Solutions PUBLIC
53 How we are doing at microscale meteorological modeling?
54 Acchievable accuracy of dynamical downscaling What is dynamical downscaling? WRF-ARW, GFS 48h + 6h spin-up, 60 levels, 27 km Example 1: comparing long-term average wind speed at the anemometer height; Campaign, Turkey (complex): Significantly reduced prediction error with increased resolution. BIAS [m/s] MAE [m/s] STDE [m/s] 3 km km /3 km
![Predicted park production [MWh/y] Acchievable accuracy of dynamical downscaling Example 2:](/docs-images/93/111532231/images/55-0.jpg "wind farm production; estimated and observed Production data compensated for: Downtime Wake")
55 Predicted park production [MWh/y] Acchievable accuracy of dynamical downscaling Example 2: wind farm production; estimated and observed Production data compensated for: Downtime Wake (based on standard wake models) Curtailed operations AEP Model only AEP Corrected using mast data MAE STDE EtotP WRF raw WRF corr 16.2% 18.2% 4.7% 8.0% 9.4% 2.7% Observed park production [MWh/y]
56 Purely downscaling of 1 o analyses
57 Downslope storm, hydraulic jump dx=100m Holton, 1992
58 Downslope storm, hydraulic jump dx=100m Data from nacelle anemometers overlaid
59 An example of sensitivity to the unknown
60 Important to know the wind profile m 120 m Actual Assumed Typical met-mast height ( ) > ( ) 2% wind speed error 5% AEP error
61 Important to know the wind profile + % over-predicted AEP Error committed if the wind shear between 40/80m is assumed to be valid up to 180m: in average 5% AEP! Rule of ( ) > ( ) 2% wind speed error 5% AEP error : 1 % AEP corresponds to 1 meur on a 100 MW wind farm
62 How does WRF-LES by do?
63 Australia 1
64 Australia 2
65 Scotland 1 avg(v) σ(v) A k Obs. data 8.1 m/s 4.3 m/s 9.1 m/s 2.0 Model 8.7 m/s 4.0 m/s 10.0 m/s 2.5
66 Scotland 1 Wind Frequency Rose Turbulence intensity Rose
67 Scotland 1 Period of low wind speed causing high turbulence intensity
68 Scotland 1
69 USA 1
70 USA 1 Scotland 1 σ(wdir) vs. Wspeed Indicates rapid direction changes Available in WRF-LES output
71 India 1
72 India 1 Observed at met-mast Vestas WRF 3km WRF-LES Not whole weather is simulated accurately But the statistics of wind speed, turbulence,... is very comparable Future development? (e.g. surface shape and characteristics,...)
73 Guess which are the measurements and which are the model results LES IS MORE!
74 Guess which are the measurements and which are the model results LES IS MORE!
75 Guess which are the measurements and which are the model results LES IS MORE!
76 Guess which are the measurements and which are the model results LES IS MORE!
77 Guess which are the measurements and which are the model results LES IS MORE!
78 Guess which are the measurements and which are the model results LES IS MORE!
79 LES* IS MORE! * L ARGE E DDY S IMULATIONS BY VORTEX WindEnergy Hamburg 2016
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