HIGH-RESOLUTION NUMERICAL SIMULATION OF WIND ENERGY RESOURCE IN HAINAN PROVINCE AND ITS OFFSHORE WATERS

XING Xu-huang; ZHU Rong; ZHAI Pan-mao; YU Wei

Abstract:

With high resolution (1 km), the distribution of wind energy resources in Hainan province and over its offshore waters is numerically simulated by using the Wind Energy Simulation Toolkit (WEST) model developed by Meteorological Research Branch of Environment Canada. Compared with observations from eight coastal anemometric towers and 18 existing stations in the province, the simulations show good reproduction of the real distribution of wind resources in Hainan and over its offshore waters, with the relative error of annual mean wind speed being no more than 9% at the 70-m level. Moreover, based on the simulated results of WEST grids that are closest to where the eight wind towers are located, the annual mean wind speeds are further estimated by using the Danish software WasP (Wind Atlas Analysis and Application Program). The estimated results are then compared with the observations from the towers. It shows that the relative error is also less than 9%. Therefore, WEST and WEST+WAsP will be useful tools for the assessment of wind energy resources in high resolution and selection of wind farm sites in Hainan province and over its offshore waters.

Get Citation+

XING Xu-huang, ZHU Rong, ZHAI Pan-mao, et al. HIGH-RESOLUTION NUMERICAL SIMULATION OF WIND ENERGY RESOURCE IN HAINAN PROVINCE AND ITS OFFSHORE WATERS [J]. Journal of Tropical Meteorology, 2010, 16(3): 292-298.

Export:

Article Metrics

HIGH-RESOLUTION NUMERICAL SIMULATION OF WIND ENERGY RESOURCE IN HAINAN PROVINCE AND ITS OFFSHORE WATERS

College of Atmospheric Sciences, Lanzhou University

Abstract: With high resolution (1 km), the distribution of wind energy resources in Hainan province and over its offshore waters is numerically simulated by using the Wind Energy Simulation Toolkit (WEST) model developed by Meteorological Research Branch of Environment Canada. Compared with observations from eight coastal anemometric towers and 18 existing stations in the province, the simulations show good reproduction of the real distribution of wind resources in Hainan and over its offshore waters, with the relative error of annual mean wind speed being no more than 9% at the 70-m level. Moreover, based on the simulated results of WEST grids that are closest to where the eight wind towers are located, the annual mean wind speeds are further estimated by using the Danish software WasP (Wind Atlas Analysis and Application Program). The estimated results are then compared with the observations from the towers. It shows that the relative error is also less than 9%. Therefore, WEST and WEST+WAsP will be useful tools for the assessment of wind energy resources in high resolution and selection of wind farm sites in Hainan province and over its offshore waters.

HTML

Reference (15)

[1]	JOHN L W, REBECCA J B, WILLIAM R B. The statisticalprediction of offshore winds from land-based data forwind-energy applications [J]. Boundary-Layer Meteor., 2001,101(3): 409-433.
[2]	LANGE B, LARSEN S E, HOJSTRUP J. The wind speedprofile at offshore wind farm sites [C]// Preprint, Dewek 2002,Wilhelmshaven: 1-4.
[3]	YUAN Chun-hong, XUE Heng, YANG Zhen-bin. Anumerical modeling study for offshore wind speed [J]. J. SolarEnergy. 2004, 25(6): 740-743.
[4]	JIANG Dong, WANG Jian-hua. Wind energy resourcesassessment in the coastal zones based on spatial informationtechniques [J]. Prog. Geography, 2004, 23(6): 41-48.
[5]	YU W, BENOIT R, GIRARD C, et al. Wind EnergySimulation Toolkit (WEST): a wind mapping system for use bythe wind-energy industry [J]. Wind Eng., 2006, 30: 15-33.
[6]	GIRARD C, BENOIT R, DESGAGNé M. Finescaletopography and the MC2 dynamics Kernel [J]. Mon. Wea. Rev.,2005, 133(6): 1 463-1 477.
[7]	TANGUAY M, ROBERT A, LAPRISE R. A semi-implicitsemi-Lagrangian fully compressible regional forecast model[J]. Mon. Wea. Rev., 1990, 118: 1 970-1 980.
[8]	THOMAS S, GIRARD C, BENOIT R, et al. A newadiabatic kernel for the MC2 model [J]. Atmos-Ocean. 1998,36(1): 241-270.
[9]	TROEN I, PETERSEN E L. The Wind Atlas model(Chapter 8) [M]. European Wind Atlas, Denmark: Ris?National Laboratory, 1989: 565-593.
[10]	KALNAY E, KANAMITSU M, KISTLER R, et al. TheNCEP/NCAR 40-year reanalysis project [J]. Bull. Amer.Meteor. Soc., 1996, 77(3): 437-471.
[11]	ZUO Hong-chao, LU Shi-hua, HU Yin-qiao. Variationtrend of yearly mean air temperature and precipitation inChina in the last 50 years [J]. Plateau Meteor., 2004, 23(2):238-244.
[12]	ZHANG Y, SPERBER K R, BOYLE J S. Climatology andinterannual variation of the East Asian winter monsoon:results from the 1979-95 NCEP/NCAR reanalysis [J]. Mon.Wea. Rev., 1997, 125(10): 2 605-2 619.
[13]	ZHANG Qiong, QIAN Yong-fu. Monthly mean surfacealbedo estimated from NCEP/NCAR reanalysis radiation data[J]. Acta Geographica Sinica, 1999, 54(4): 309-317.
[14]	WANG Shu-yu. The studies of East Asia regional climatemodeling and soil moisture initialization [D]. Beijing: Instituteof Atmospheric Physics, Chinese Academy of Sciences. 2003.
[15]	TANG Jian-ping, SU Bing-kai, ZHAO Ming, et al. Longterm climate change numerical simulation in east Asia [J].Acta Meteor. Sinica, 2004, 62(6): 752-763.

HIGH-RESOLUTION NUMERICAL SIMULATION OF WIND ENERGY RESOURCE IN HAINAN PROVINCE AND ITS OFFSHORE WATERS

Abstract:

References

Get Citation+

Share Article

Article Metrics

Proportional views

Manuscript History

Online:

通讯作者: 陈斌, bchen63@163.com