EWEC 2009, 19 March 2009 – Dierer et al.: Modelling the risk of icing
EWEC 2009: Modelling wind flow 19 March 2009
quaModelling the risk of icing
Dr. Silke Dierer1
René Cattin1
Dr. Alain Heimo1
Bjørn Egil Nygaard2 Kristiina Säntti3
1 METEOTEST, Switzerland2 Norwegian Meteorological Institute, Norway3 Finnish Meteorological Institute, Finland
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EWEC 2009, 19 March 2009 – Dierer et al.: Modelling the risk of icing
Icing and wind energy
• Icing interferes with aerodynamics of blades => reduced power production.
• Icing causes unbalanced mass => faster fatigue of material.
• Icing might cause ice throw => safety risk
• Thus, knowledge about icing is important:
• for planning = icing maps• during operation = forecasts
T. Wallenius: The effect of Icing on energy production losses of wind turbines with different control strategies, EWEC 2008
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EWEC 2009, 19 March 2009 – Dierer et al.: Modelling the risk of icing
Risk of icing in Europe: icing days per year
Source: Tammelin, B., Cavaliere, M., Holttinen, H., Morgan, C., Seifert, H., Säntti, K., Wind Energy Production in Cold Climate, Meteorological Publications No. 41, Finnish Meteorological Institute, Helsinki. 2000.
Icing frequency [days/year] Annual loss of production
< 1 Not significant
1 – 10 small
10 – 30 5 – 15%
30 – 60 15 – 25%
> 60 > 25%
T. Laakso, H. Holttinen, G. Ronsten, L.Tallhaug, R.Horbaty, I. Baring-Gould, A. Lacroix, E. Peltola, B. Tammelin, 2005: State-of-the-art of wind energy in cold climate, IEA Wind Annex XIX, 53 p. http:\arcticwind.vtt.fi, date of access 12.3.2009
No icing< 1 day/year2 -7 days/year
8 – 14 days/year15 - 30 days/year> 30 days/year
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EWEC 2009, 19 March 2009 – Dierer et al.: Modelling the risk of icing
COST-727 “Measuring and forecasting atmospheric icing on structures”
Sensor Technology
MeteorologigalMeasurements
Input
MODEL
Output
Application
ForecastingDesign Ice Loadson Structures
Power Losses ofWind Turbines
IcingMeasurements
Measurements
Modelling
Aim of the current study:Coupling a weather model with an icing algorithm and test for different regions improve method for icing map calculation Evaluate the potential of icing forecasts
• Aim: – improved understanding of
in-cloud icing, wet snow and freezing rain in different European regions
– enhance the potential to observe, monitor and forecast icing
• Method:– In-situ icing measurements at
six stations in different regions of Europe
– Development and evaluation of icing models
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EWEC 2009, 19 March 2009 – Dierer et al.: Modelling the risk of icing
Overview
• Method and models
• Results Luosto, Finland
• Results Gütsch, Switzerland
• Icing forecasts Schwyberg, Switzerland
• Summary
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EWEC 2009, 19 March 2009 – Dierer et al.: Modelling the risk of icing
Method and models
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EWEC 2009, 19 March 2009 – Dierer et al.: Modelling the risk of icing
Model system for icing simulations
Algorithm to calculate icing on structures (Makkonen, 2000)
Wind, temperature, cloud and rain water
Simulated ice load
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EWEC 2009, 19 March 2009 – Dierer et al.: Modelling the risk of icing
Mesoscale weather model WRF
• Up-to-date mesoscale atmospheric model for:– Operational weather forecasts– Research purposes
• Application range:– Starting from large eddy simulations: Δx = 100m– Up to regional climate simulations: Δx = 100km
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EWEC 2009, 19 March 2009 – Dierer et al.: Modelling the risk of icing
Algorithm for calculating icing on structures (Makkonen, 2000)
• Model by Makkonen (2000) calculates ice load on a cylinder caused by cloud droplets accretion
• Input:– cloud water content– cloud droplet concentration– wind– temperature
• Output:– ice mass
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EWEC 2009, 19 March 2009 – Dierer et al.: Modelling the risk of icing
Results Luosto, Finland
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EWEC 2009, 19 March 2009 – Dierer et al.: Modelling the risk of icing
Luosto, 23 – 25 December 2007:
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EWEC 2009, 19 March 2009 – Dierer et al.: Modelling the risk of icing
Luosto, 21 – 25 December 2007: time series of measured wind, temperature and ice load
• WRF simulation at 800m grid size• ECMWF data as initial and boundary data• Cloud droplet number concentration: est. 75 1/cm3
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EWEC 2009, 19 March 2009 – Dierer et al.: Modelling the risk of icing
Luosto, 23 – 25 December 2007: time series of measured and simulated ice load
WRF simulation at 2.4 km grid size WRF simulation at 0.8 km grid size
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EWEC 2009, 19 March 2009 – Dierer et al.: Modelling the risk of icing
Results Gütsch, Switzerland
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EWEC 2009, 19 March 2009 – Dierer et al.: Modelling the risk of icing
Positions of icing measurements in Switzerland
Prevailing wind direction22 – 24 November 2007
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EWEC 2009, 19 March 2009 – Dierer et al.: Modelling the risk of icing
Gütsch, 23 November 2007, 08 UTC: vertical cross section of hydrometeors
Position of Gütsch site
Wind direction
South North
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EWEC 2009, 19 March 2009 – Dierer et al.: Modelling the risk of icing
Gütsch, 22 - 24 November 2007: time series of simulated ice load - WRF at Δx = 2.4 and 0.8 km
WRF simulation, Δx=2.4 km
Maximum ice load 0.0 kg/m Maximum ice load 1.3 kg/mWRF simulation, Δx=0.8 km
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EWEC 2009, 19 March 2009 – Dierer et al.: Modelling the risk of icing
Gütsch, 22 - 24 November 2007: sensitivity regarding droplet number concentration
WRF, Δx=800m, Nd = 35 1/cm3
Maximum ice load 1.3 kg/m Maximum ice load 0.9 kg/mWRF, Δx=800m, Nd = 70 1/cm3
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EWEC 2009, 19 March 2009 – Dierer et al.: Modelling the risk of icing
Positions of icing measurements in Switzerland
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EWEC 2009, 19 March 2009 – Dierer et al.: Modelling the risk of icing
Icing forecasts for Schwyberg, Switzerland using the COSMO model
Schwyberg,12.11.2008
Schwyberg,21.11.2008
Schwyberg,11.12.2008
Ice load is simulated driving the Makkonen model with results of the Swiss operational weather forecast model COSMO-2 at 2.2 km grid size
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EWEC 2009, 19 March 2009 – Dierer et al.: Modelling the risk of icing
Summary
• Good results regarding – capturing icing events– the timing of icing events
• Quantitative forecast of ice load less precise – Accuracy of measurements uncertain – Difficulties to define the most suitable grid box
• Strong sensitivity regarding horizontal resolution and cloud droplet concentration
• First results of icing forecasts for Switzerland indicate that there is a potential to forecast icing events
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EWEC 2009, 19 March 2009 – Dierer et al.: Modelling the risk of icing
Thank you for your attention