WeatherTech

1. EstimationofProductionLossesDueto Icing – A CombinedField Experiment and NumericalModellingEffort Stefan Söderberg(1), Magnus Baltscheffsky(1), Hans Bergström(2) (1),WeatherTech Scandinavia AB, (2) Uppsala University WeatherTech

2. WeatherTech Swedish research project: VindforskV-313, Wind power in cold climates - develop methods for estimating the icing climate and production losses due to icing. Tools: - Observations wind speed, temperature, ice load, wind farm data - Ice load model ISO 12494:2001 – Atmospheric icing on structures - Mesoscale models: WRF, COAMPS® (US Navy), AROME (e.g., SMHI), different microphysics and PBL schemes

3. WeatherTech Icing conditions does not necessarily mean “cold climate conditions”. Icing conditions: - Temperatures below freezing point - Clouds (or fog) containing water droplets - A surface to freeze at

4. WeatherTech Observations Icemeasuringdevices Holoptics (optical sensor) 11 sites, 3 winterseasons:telecommunication masts, mettowers, and windturbines. Ice Monitor (load cell)

5. WeatherTech Observations Icemeasuringdevices Holoptics (optical sensor) Measuringice is not a trivial task! - Optical sensor coveredby ice -Uneven distribution ofice on loadcell and often a spiky signal Ice Monitor (load cell)

6. WeatherTech Ice accretion model

7. WeatherTech Numerical experiment setup Initial and lateral boundary conditions: - i) NCEP Final Analysis (FNL from GFS) ii) ERA Interim iii) NCEP/NCAR Reanalysis Vertical grid configuration: - 11 levels in the lowest 300 m Horizontal grid configuration: - nested grids Outer nest: 27 x 27 km2 3:1 nest ratio Innermost nest: 1 x 1 km2 Example of model domains

8. WeatherTech Model evaluation Example of observed and modelled ice load (all condensates)

9. WeatherTech Model evaluation – brief summary • “Standard meteorological variables (wind, temperature, pressure) are well captured by all three models (AROME, COAMPS®, WRF). • Timing of icing events are quite well captured (accreation, melting and sublimation). • Modelled ice load is often underestimated.

10. WeatherTech Production loss estimates I Power 3D power curves Power production as a function of wind speed and ice load. Power curves derived from wind farm production and ice load measurements. Wind Speed Ice load Production loss often underestimated – is the modelled/observed ice load representative for icing on a wind turbine?

11. Active icing WeatherTech Production loss estimates II 3D power loss curves Active icing: Power loss as a function of wind speed and icing rate. Passive icing: Power loss as a function of wind speed and ice load. Derived from observations and mesoscale model data. Power loss /%) Power loss /%) Passive icing Ice load Icing rate (g/h) Wind Speed Wind Speed Improvement but still under-estimated production loss.

12. WeatherTech Production loss estimates III Multidimensional power loss functions for individual turbines Power loss as a function of wind speed, wind direction, icing rate, ice load, temperature, etc. Derived from turbine data and mesoscale model data.

13. WeatherTech Power loss model evaluation (hourly values)

14. WeatherTech Power loss model evaluation (hourly values) Reducedforecasterrorwhentaking icing intoaccount.

15. WeatherTech Power loss model evaluation

16. WeatherTech Icing climate Wind index Long-Term Reference 30+ yearsofhourlyvaluesofwindspeed, temperature, cloudwater etc. from WRF runs on a 9x9 km2modelgrid.

17. WeatherTech Production index Icing climate “Yearly” (May 1st –April 30th) deviations from 30-year mean There is a substantial yearly variation in production and production losses. Production losses in individual years can be twice as large as the long term mean. Production loss index

18. WeatherTech Conclusions • Measuring ice is not trivial. State of the art instruments are not accurate enough. • Modelling ice load is not straight forward. The end result depend on which model that is used and how the model is set up. • The timing of the icing events are quite well captured. • The multidimensional power loss model looks promising for site assessment and forecasting. • In icing climate studies, it is likely that some 20-30 years are needed to capture the variability in the icing climate.

19. WeatherTech Thankyou for yourattention Stefan Söderberg mobile: +46 (0)70 393 22 60 email: stefan.soderberg@weathertech.se V-313 Windpower in coldclimates Reportwill be publishedhere (likely in March 2013): http://www.elforsk.se/Programomraden/El--Varme/Vindforsk/reports/reports_area_1_2/