in the Western North Pacific Søren Ott
Outline Tropical cyclones and wind turbines Modelling extreme winds Validation Conclusions Cat. 4 tropical cyclone IVAN 15 Sept 2004 at landfall near Luisiana, USA (NASA/GSFC) 2 Risø DTU, Technical University of Denmark
EU-ASEAN Wind project Feasibility assessment and capacity building for wind energy development in the Philippines, Vietnam and Cambodia. Project period: Feb. 2005 Dec. 2006 Risø National Laboratory (coordinator) Innovation Énergie Développement Mercapto Consult PNOC Energy Development Corporation Institute of Energy Ministry of Industry, Mines and Energy Denmark France Denmark Philippines Vietnam Cambodia The project is financially supported from the EC-ASEAN Energy facility through the ASEAN Energy Centre in Jakarta. Contract 125-2004. 3 Risø DTU, Technical University of Denmark
Damaged wind farms Gujarat, India 1998 (left and top) 4 Risø DTU, Technical University of Denmark Japan: Miyakojima wind farm after being hit by a typhoon Sept. 2003 (right)
NorthWind, Bangui Bay, Philippines This wind farm have survived two typhoons but with damage to cabling (flooding) 57 km 69 kv transmission line to substation Power back-up for yaw system 5 Risø DTU, Technical University of Denmark Photo by NorthWind
Geographical distribution of tropical cyclones Taiwan NW Pacific average 17 TCs per year 6 Risø DTU, Technical University of Denmark
Sea water temperatures May 2001 T > 26.5 C Source: MODIS Ocean Group, NASA/ GSFC and Miami University) 7 Risø DTU, Technical University of Denmark
Tropical cyclone anatomy A rotating collection of thunderstorms over a warm sea surface. Tropical depression <17 m/s Tropical storm 17-32 m/s Tropical cyclone >32 m/s (hurricane, typhoon) Average 48 TCs per year globally (20-35 years data) 8 Risø DTU, Technical University of Denmark
Klosa/Nock-ten 9 Risø DTU, Technical University of Denmark
Taiwan orography based on data from NASA 10 Risø DTU, Technical University of Denmark
WAsP Engineering WAsP Engineering is a program to support load calculations on wind turbines. The output includes o o o Extreme wind climate Wind shear and profiles Turbulence over complex terrain. 11 Risø DTU, Technical University of Denmark
Estimating the fifty year wind U 1Y : annual max. 10 min. average wind speed Assumptions: U 1Y is Gumbel distributed U 1Y is derived from best track data using Holland s model. 12 Risø DTU, Technical University of Denmark
NCEP/NCAR re-analysis 13 Risø DTU, Technical University of Denmark
Best track data Typhoon data derived from satellite images Available from Joint Typhoon Warning Center (JTWC) Hawaii Japanese Meteorological Agency (JMA) Tokyo Detailed data (position, P c, V max, R 50knt ): 2001-2003 (JTWC) 1977-2008 (JMA) 14 Risø DTU, Technical University of Denmark
Typhoon best track data 1977-2005 2006 2005 Data Japan Meteol. Agency JMA 2004 Only parts of tracks with V max > 50 knots are shown 15 Risø DTU, Technical University of Denmark
From image to wind speed The Dvorak method used to estimate P c and V max JTWC and JMA get different results! +50% JMA - JTWC Intercomparison 2001-2003 16 Risø DTU, Technical University of Denmark Dvorak
Pc-Vmax relations Shea+Gray (1973) JMA JTWC Atkinson+Holliday (1973) 17 Risø DTU, Technical University of Denmark
Gradient wind 2 V g r = ρ 1 dp dr fv g 18 Risø DTU, Technical University of Denmark
Holland s Model Assumes gradient balance and prescribes the pressure profile. Model parameters: Central pressure P c Eyewall radius R w Peakedness B From track data: Central pressure P c Maximum wind V max 50 knots radius R 50 Centre position V 2 (r) = K m 2 B (P n - P c ) (R w /r) B exp[- (R w /r) B ] P n ~1010 hpa ~1.15 kg/m 3 K m ~0.7 19 Risø DTU, Technical University of Denmark
Determination of U 50 track shortest distance observation point Find shortest distance from observation point to track. Find max wind speed from track data using Holland s model Make a list of annual maxima Fit a Gumbel distribution F(u) = exp(-exp(-(u- )/ ) U 50 = log 50 Repeat for obs. points on a 1 x1 grid Make a map 20 Risø DTU, Technical University of Denmark
Extreme wind atlas for Western N Pacific U 50 10 min average 10 m above sea based on JMA typhoon tracks 1977-2005 21 Risø DTU, Technical University of Denmark
Comparison with Philippine Structural Code 3 sec gust 10 m height land (3 cm) 10 min av 10 m height over sea 22 Risø DTU, Technical University of Denmark
Validation Batanes met station Manual reading of V max 23 Risø DTU, Technical University of Denmark
50 year wind at Batanes data: 70 m/s tracks: 65 m/s stat. error: 7 m/s 24 Risø DTU, Technical University of Denmark
Synoptic met station data 49 year maximum wind speed at 48 synoptic met stations 25 Risø DTU, Technical University of Denmark
Synoptic data comparison Maximum 49 year wind speed: model vs. synoptic station data 26 Risø DTU, Technical University of Denmark
Tropical storm near Sta. Ana in 2005 SW NE 27 Risø DTU, Technical University of Denmark
Conclusions U 50 has been estimated from best track data in the Western North Pasific The method may have systemetic errors, but is ok for comparative studies Fair agreement with ground data Report: Søren Ott: Extreme winds in the Western North Pacific. Risø-R-1544(en), 2006. Thank you for your attension! 28 Risø DTU, Technical University of Denmark