Winterwind, International Wind Energy Conference, February 2012, Skelleftea, Sweden

1. Evaluation of WRF mesoscale model for icing events characterization: Some insights on model performance Pau Casso (1) Gil Lizcano (1) Pep Moreno (1) Josep Calbó (2) Alain Ochoa de Retana (3) 1) Vortex, Barcelona, Spain(2) University of Girona, Girona, Spain (3) Gamesa Energía, Zamudio, Spain EWEA 2012 Annual Event, April 2012, Bella Center, Copenhaguen, Denmark Winterwind, International Wind Energy Conference, February 2012, Skelleftea, Sweden

2. Outline Icing Occurs Motivation Model Setup Results Conclusions EWEA 2012 Annual Event, April 2012, Bella Center, Copenhaguen, Denmark

3. Icing Occurs • Icing really occurs and implies: • Health and Safety issues • Loss of production • Increased loads & damage • Increased noise • Availability • O&M • Life-time Figure1: Alpine site Test Gütsch site in Switzerland EWEA 2012 Annual Event, April 2012, Bella Center, Copenhaguen, Denmark

4. Icing is a Problem Not yet well defined how to cope with Icing in the wind industry: -Manufacturers: Developing heating and de-icing systems. Strong competence. -Developers: Lots of questions arise regarding guarantees from manufacturers and production losses. -Consultancies: Not clear how to include Icing uncertainties in projects evaluations. EWEA 2012 Annual Event, April 2012, Bella Center, Copenhaguen, Denmark

5. Motivation - Rapid increase of wind energy markets in Cold Climates - Power production loss estimations due to icing are difficult - Lack of observed icing conditions are a constant EWEA 2012 Annual Event, April 2012, Bella Center, Copenhaguen, Denmark

6. Motivation • Hindcast modeling solutions have been proved as skillful alternatives to represent wind regime and temperature at near windfarm resolution. • Anemometry and turbine alarms data from Gamesa was available at 6 wind farms with detected icing events. EWEA 2012 Annual Event, April 2012, Bella Center, Copenhaguen, Denmark

7. Model Setup and Configuration Purpose: Detect icing events with a modeling chain with NO use of on-site measured data WRF mesoscale model -> Wind, Temp., cloud and rain water Algorithm to calculate icing on structures (Makkonen, 2000) Simulated ice load and ice episodes EWEA 2012 Annual Event, April 2012, Bella Center, Copenhaguen, Denmark

8. Model Setup and Configuration • STEP 1 - Cold weather events detection • 1km resolution WRF model hindcasts over 10 years • Driven by NCEP/CFS reanalysis at 0.5 degrees • Thompson microphysics scheme Output used to select potential icing events based on crossed distribution of humidity and temperature. Figure 1 Nested domains that define downscaling approach at a 1Km WRF temperature and moisture characterization EWEA 2012 Annual Event, April 2012, Bella Center, Copenhaguen, Denmark

9. Model Setup and Configuration STEP 2 – Icing rate calculation and wind distributions -High 100m WRF resolutions during icing episodes pre-selected in Step1. -Output used to feed Makkonen icing accretion model: calculates ice load on a cylinder caused by cloud droplets accretion. Results: Estimation of icing events duration based on icing rate threshold of 10 gr/h. Analysis of wind distributions during icing episodes. EWEA 2012 Annual Event, April 2012, Bella Center, Copenhaguen, Denmark

10. Model Setup and Configuration • The model chain WRF 1km → WRF 100m → Makkonen is applied to 6 sites. • Available anemometry data from Gamesa at 6/6 wind Farms. • Available turbine-stop alarms data due to icing at 3/6 wind Farms. EWEA 2012 Annual Event, April 2012, Bella Center, Copenhaguen, Denmark

11. Results Icing events occurrences match EWEA 2012 Annual Event, April 2012, Bella Center, Copenhaguen, Denmark

12. Results • Icing events occurrences match • Vortex relevantly matches the icing occurrences on a mean value when compared to anemometry data. • In relation to turbine stops, results are discouraging. • Lack of knowledge between anemometry and turbines availability in icing conditions. EWEA 2012 Annual Event, April 2012, Bella Center, Copenhaguen, Denmark

13. Results Wind distribution during icing events Case 1: High wind speed icing conditions Strong wind conditions under icing episodes Indication of significant production loss Wind Speed Distribution during icing conditions Mean Wind Speed Distribution EWEA 2012 Annual Event, April 2012, Bella Center, Copenhaguen, Denmark

14. Results Wind distribution during icing events Case 1: High wind speed icing conditions Wind Direction during icing conditions Mean Wind Direction Icing conditions correspond to main direction Indication of significant production loss EWEA 2012 Annual Event, April 2012, Bella Center, Copenhaguen, Denmark

15. Results Wind distribution during icing events Case 2: Low wind speed icing conditions Wind Speed Distribution during icing conditions Mean Wind Speed Distribution Low wind speed conditions during icing episodes Not very relevant production losses EWEA 2012 Annual Event, April 2012, Bella Center, Copenhaguen, Denmark

16. Results Wind distribution during icing events Case 2: Low wind speed icing conditions Wind Direction during icing conditions Mean Wind Direction Icing conditions do NOT correspond to main direction Not very relevant production losses but guide for security issues EWEA 2012 Annual Event, April 2012, Bella Center, Copenhaguen, Denmark

17. Conclusions The modeling chain shows an interesting ability to track icing episodes specially against anemometry data. Very poor correlation between modeling and turbine availability. Lot of work to do. Need of specific turbine model. Very encouraging results regarding the characterization of wind distributions under icing conditions. Promising results to estimate production losses. Interesting guide for designing security and accessibility issues. EWEA 2012 Annual Event, April 2012, Bella Center, Copenhaguen, Denmark

18. Conclusions Thank you for you attention. EWEA 2012 Annual Event, April 2012, Bella Center, Copenhaguen, Denmark