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