CFD SIMULATIONS OF WAKE EFFECTS AT THE ALPHA VENTUS OFFSHORE WIND FARM

Transcription

1 CFD SIMULATIONS OF WAKE EFFECTS AT THE ALPHA VENTUS OFFSHORE WIND FARM Annette Westerhellweg, Thomas Neumann DEWI GmbH, Ebertstr. 96, Wilhelmshaven, Germany Phone: +49 (0) Fax: +49 (0) Summary Since August 2009, the first German offshore wind farm Alpha Ventus is operating close to the offshore wind measurement platform FINO1. Within the RAVE OWEA research project, we have evaluated the wind turbine wake effects at FINO1 and have compared the measurements with CFD simulation results. The ambient wind conditions were estimated. The ambient wind speed was approximated by the nacelle anemometer wind data from one Alpha Ventus wind turbine. The turbulence intensity increase was determined by comparison with the general ambient turbulence intensity. The measured wind speed reductions show high agreement with the CFD simulation results. The turbulence increase was underestimated by the CFD model. The atmospheric stability has a measurable effect in the measurement of the wind conditions in wake. Under stable conditions a more pronounced wind speed decrease is measured in the wake of the wind turbines of Alpha Ventus. 1. Introduction In the frame of the OWID research project (OWID=Offshore WInd Design parameter) a CFD model for offshore was developed [3]. One task of the RAVE OWEA research project [1] is the evaluation of wake effects in the wind farm Alpha Ventus and the comparison with results of the CFD simulation model. 2. Wind Farm Site The wind farm Alpha Ventus (see Figure 1) consists of 6 Repower 5M with a rotor diameter of 126m (AV01-AV06) and 6 AREVA M5000 with a rotor diameter of 116m (AV07-AV12). The measurement platform FINO1 is located 405m to the west of wind turbine AV04. Figure 1: Locations of the offshore platform FINO1 and the first German wind farm Alpha Ventus. 1/8

2 3. CFD model DEWI performs CFD simulations of the wake wind fields using a parabolic RANS (Reynolds-averaged Navier-Stokes) Solver. This RANS wind farm wake model was developed and validated by DEWI in the frame of the OWID research project [3] and has been used by DEWI for the assessment of large offshore wind farms since then. The turbulence is modelled with the k-ε turbulence model using the original model parameters [6]. The wind turbines are considered as actuator discs. Boundary conditions of the model (turbulence intensity, vertical wind profile) are set according to the average conditions measured at the offshore platform FINO1. The CFD model solves the Reynolds Averaged Navier-Stokes Equations in parabolic mode using the commercial CFD software Phoenics [4]. For a model description refer to [2]. The CFD simulations for Alpha Ventus were performed using a Cartesian grid. The grid spacing within the wind farm area has been set to 10m in stream-wise, cross-stream and upward direction. The directional resolution was 2 degree. The effect of the wind turbines on the flow depends on the hub height, the rotor diameter and the ct curve. The reduction of wind speeds at the rotor level is determined approximately from the ct-curve and the actuator disc model. Figure 2 show the CFD results for the wind speed at hub height relative to an inflow wind speed of 10m/s. Figure 2: CFD results for the wind speed at hub height relative to an inflow wind speed of 10m/s. The wind direction is east. 2/8

3 4. Preparation of the Measurement Data Wind speed and wind direction data of the FINO1 platform from the height level of 91.5m have been assessed. A mast correction of both data has been applied. For the assessment of the wind speed reduction in the wind turbine wakes, the free wind speed is needed. As no second mast is installed on the opposite wind farm side, data of the nacelle anemometer of wind turbine AV12 have been evaluated and used as a measure for the undisturbed wind speed. AV12 shares a common free wind direction sector with FINO1 [184 ; 250 ]. Data with a wind direction within this wind direction sector have been used to calculate a nacelle anemometer calibration function depending on wind speed. Afterwards, this calibration function has been applied to the nacelle anemometer data of AV12 within the wind direction sector [12 ; 260 ] to gain an approximation of the free wind speed in these directions. Figure 3: Calibration function to correct the nacelle anemometer data of AV12 to generate free wind speed data. In each wind direction sector only those data sets have been evaluated when all wind turbines in that sector were in full operation. Depending on the data availability the evaluation is divided in different direction sectors: direction sector evaluation period Evaluation sector (free sector for AV12) Wake of AV1-AV jun2010-jan2011 Wake of AV7-AV9 and AV nov2010-jan2011 No wake - reference sector jun2010-jan2011 Table 1: Evaluation periods. The wake effects of the Repower wind turbines (AV01-AV06) were evaluated for the period Jun2010- Jan2011 whereas the wake effects of the AREVA wind turbines (AV07-AV12) were evaluated for the period Nov2010-Jan2011. Only data sets with AV07-AV09 and AV12 in operation (status signal 7) were assessed. The wake sectors of AV10 ( ) and AV11 ( ) were excluded from the evaluation because of a too small data base. The wind direction sector [174 ; 260 ] has been evaluated as reference sector. The ratio v free /f FINO should be 1 for the wind directions without any wake. The measurement period did not cover a whole year, but only a period of 8 or 3 months respectively. Due to the distribution of different atmospheric stratification in the year, the results do not represent the average conditions. Therefore different stability cases have been evaluated separately. 5. Wind Speed Reduction in the Wake CFD simulations were performed for ambient hub height wind speeds of 8 m/s, 10 m/s, 12 m/s and 16 m/s. Measured wind data have been evaluated within wind speed intervals of 4 m/s width, each 3/8

4 interval centred at one of the 4 simulated wind speeds. These very large wind speed intervals have been necessary in order to ensure reliable statistics within each combined wind speed and wind direction interval. Figure 4 shows the wind speed reduction versus wind direction for different wind speed intervals. The wind direction sectors of the wakes of the single wind turbines of Alpha Ventus are marked in the figure. Wind turbine AV04 is located at a distance of 405m from FINO1, which represents a distance of 3.2 rotor diameters (D). In this wind direction (90 ), three wind turbines are in line with FINO1. The multiple wakes of the three wind turbines AV4-AV6 are met well by the CFD simulations for all assessed wind speed intervals. The wakes of the wind turbines at a distance of about 900m, AV1 and AV7 (7.2D and 7.5D) are met by the CFD simulations for all regarded wind speed intervals as well. The wake effects of the wind turbine AV2, located at a distance of about 1.5km, are met reasonable for some wind speed intervals. The wind speed reduction in wakes of wind turbines at larger distances are overestimated by the CFD simulations. Figure 5 shows the wind speed reduction for different wind speed intervals. Whereas the CFD results show a maximum wind speed deficit in the wake of AV4 of 40% for ambient hub height wind speeds of 8 m/s and 10m/s, the maximum wind speed decrease is only 20% for 16 m/s. The measurements are approximately in the same range. At wind directions > 174, there is no influence of Alpha Ventus on the FINO1 measurements. However, this wind direction shows large scatter and a mean value deviating from unity indicating the range of uncertainty of this evaluation method. AV01 AV02 AV03 AV09 AV07 AV04 AV08, AV12 Figure 4: Wind speed reduction in the wake of Alpha Ventus, CFD simulation results and evaluated measurements at FINO1. CFD simulations are performed for the free wind speed 8m/s, from the measurements results of the wind speed interval of 8 m/s +/- 2m/s are shown. For the wake evaluation of the wind turbines AV10 and AV11 not enough data were available, therefore the sectors of their wakes are excluded from the evaluation. 4/8

5 Figure 5: Wind speed reductions in the wake of Alpha Ventus, CFD simulation results and evaluated measurements at FINO1. CFD simulations have been performed for the stated ambient hub height wind speed. The graphs on the left hand side show bin averages (2 degree bins). The graphs on the right hand side show bin averages (5degree bins) and single measured values. 6. Wind Speed Reduction in the Wake for different Stratifications For the period June 2010 until January 2011 (8 months), water temperature data at a depth of -3 m and air temperature data at a height of 30m have been evaluated. Different stratifications have been defined as follows: Unstable: T 30m < T -3m -1 C, Stable: T 30m > T -3m +1 C and 5/8

6 Neutral: T -3m -1 C < T 30m < T -3m +1 C. Table 2 shows the number of data sets considered in each stability class. evaluated period: Jun10-Jan11 Found data sets 8m/s [6;10m/s]: 3636 stable: T(air30m)>T(water-3m)+1K 489 unstable: T(air30m)<T(water-3m)-1K 2308 neutral: T(water-3m)-1K<T(air30m)<T(water-3m)+1K 839 Table 2: Data availability for different stratifications. Figure 6 shows the wind speed reductions for the different stratification classes. For the wake sectors of AV07-AV12, only data for unstable stratifications could be evaluated. For the wakes of AV1-AV6, it can be observed that wakes of the wind turbines adjacent to FINO1, AV1 and AV4, are met best by the CFD simulation results for neutral conditions. During stable conditions, the measured wind speed reduction is higher than the simulated reduction, whereas during unstable conditions the measured wind speed reduction is lower than the reduction simulated with the CFD model. This is a result of the fact that the CFD model is designed for neutral conditions. All data 8m/s Jun2010-Jan2011: Neutral: Unstable: Stable: Figure 6: Wind speed reduction in the wake of Alpha Ventus for an ambient wind speed 8m/s for different stability cases. 6/8

7 7. Turbulence in the Wake The turbulence intensity has been assessed for different ambient wind speeds and different stability classes. For unstable as well as for stable stratifications, the CFD simulation underestimates the increase of the turbulence intensity in the wind turbine wakes. The CFD calculations were set up to meet average ambient turbulence conditions of FINO1. But, at FINO1 the turbulence intensity is not uniform but shows a dependency on the wind direction [5]. However the directional differences are only small (about in the range of 3%) compared to the turbulence increase in the wind farm wake. So the differences in the ambient turbulence intensity are not regarded here. As well it has not been considered that the ambient turbulence intensity differs for different stability cases with lower turbulence intensity for stable and higher turbulence intensity for unstable stratification, visible here for the wind direction sector not concerned by Alpha Ventus (dir>174 degree). All data 8m/s Jun2010-Jan2011: Neutral: Unstable: Stable: Figure 7: Turbulence intensity in the wake of Alpha Ventus for a free wind speed 8m/s for different stability cases. 7/8

8 8. Conclusions Wake effects are very distinctively measurable at FINO1 in both forms: wind speed decrease and turbulence intensity increase. As there is no measurement at the east side of Alpha Ventus (opposite to FINO1), these effects can only be measured indirectly: The ambient wind speed can be approximated by a nacelle anemometer wind signal. The turbulence intensity increase can only be determined by comparison with the general ambient turbulence intensity. Despite of the uncertainties of the assessment method it offers one of a few possibilities for a quantitative evaluation of the wake of state-of-the-art 5 MW wind turbines. For the wind speed reduction, good agreement between measurements and simulations can be found regarding the wakes of the wind turbines closest to FINO1 (in about 400m and 900m distance) for all regarded wind speed intervals. For the wakes of wind turbines in larger distance (about 1.5km), and for wind turbines further away, the measured wind speed decrease is, on average, lower than the simulated decrease. With respect to the turbulence intensity increase, the CFD simulation underestimates the turbulence intensity increase. The atmospheric stability has a measurable effect in the measurement of the wind conditions in wake. Under stable conditions a more pronounced wind speed decrease is measured in the wake of the wind turbines of Alpha Ventus. 9. Outlook The assessment was constrained by the fact that no free wind speed data was available but had to be generated from the nacelle anemometer data. An installation of a Lidar device on the substation of the wind farm Alpha Ventus would enlarge the possibilities to measure the wake effects, regarding both, the wind speed decrease and the turbulence increase. A CFD model can be employed for the assessment of the farm efficiency or the generation of power output matrices for the continual operational control of the single wind turbines in the wind farm. A further validation of the CFD model based on production data is planned. 10. Acknowledgements This work is part of the research project RAVE-OWEA Verification of Offshore-WEA which is funded by the German Federal Ministry for the Environment, Nature Conservation and Nuclear Safety (BMU). In particular we would like to thank Repower and AREVA for their support. 11. References [1] RAVE: Research at Alpha Ventus, [2] V. Riedel, T. Neumann: RANS-Modelling of Wind Flow through Large Offshore Wind Farms, Proceedings of the European Wind Energy Conference 2007, Mailand. [3] T. Neumann, V. Riedel, K. Grigutsch: Evaluation of Offshore Wind Design Parameter from FINO1-Data (OWID-Report), Proceedings DEWEK 2008, Bremen. [4] Phoenics Software, [5] A. Westerhellweg, B. Canadillas, T. Neumann: Direction Dependency of Offshore Turbulence Intensity in the German Bight. DEWEK 2010, Bremen. [6] Launder, B.E., Spalding, D.B.: The numerical computation of turbulent flows, Comp. Meth. In Appl. Mech. & Eng., Vol.3, pp269, /8