A numerical model system is built which is suitable for regional wind energy resource assessment and is composed by mesoscale meteorological model MM5, microscale module Calmet and calculation module of wind energy resource parameter. By using the model system, wind energy resource of littoral area in Jiangsu Province and Jiuquan area in Gansu Province are numerically simulated hour by hour with a fine resolution of 1 km×1 km. Littoral area in Jiangsu Province stands for Chinese littoral enrichment area of wind energy resource, and Jiuquan area in Gansu Province stands for north enrichment area in the condition of complex terrain. The model system is evaluated by comparisons between observational datum of wind mast in simulation area and simulation datum. The comparisons indicate that the wind energy resource distribution of the two areas is well simulated by the model system, and the simulation results of the annual average wind speed, the direction frequency of wind and wind power agree well with the observational datum. The comparisons between simulation results and observations of Jiuquan area in Gansu Province are better than that of littoral area in Jiangsu Province. Hence, the wind energy resource assessment under different terrain conditions is well numerically simulated by the model system. And the following results are indicated by the analysis of annual average wind speed and wind power, annual effective hour, and annual energy production: the wind energy resource of off-shore in Jiangsu Province is richer than that of on-shore, and it is richer from north to south; the wind energy resource of the central basin area in Jiuquan area is very rich as where is in the area of south-north facing high mountains.
ZHOU Rong-wei, HE Xiao-feng, ZHU Rong
. Application of MM5/Calmet Model System in Wind Energy Resource Assessment[J]. JOURNAL OF NATURAL RESOURCES, 2010
, 25(12)
: 2101
-2113
.
DOI: 10.11849/zrzyxb.2010.12.011
[1] American Wind Energy Association, Global wind energy market report . http: //www.awea.org/pubs/documents/globalmarket2004. pdf. 2003.
[2] 施鹏飞. 国内外风电持续迅猛发展[J]. 中外能源, 2009, 14(1): 36-40.
[3] Troen I, Petersen E L. European Wind Atlas [M]. Roskilde: Risoe National Laboratory, 1989.
[4] 薛桁, 朱瑞兆, 杨振斌, 等. 中国风能资源贮量估算[J]. 太阳能学报, 2001, 22(2): 167-170.
[5] 龚强, 袁国恩, 张云秋, 等. MM5模式在风能资源普查中的应用试验[J]. 资源科学, 2006, 28(1): 145-150.
[6] 李艳, 王元. 岛屿型复杂地形地貌条件下有效风能分布的甚高分辨率数值模拟[J]. 太阳能学报, 2007, 28(6): 663-669.
[7] Frank H P, Rathmann O, Mortensen N G, et al. The numerical wind atlas-the KAMM/WAsP method . http: //www. risoe. dk/rispubl/VEA/veapdf/ris-r-1252. pdf. 2001.
[8] Brower M C, Bailey B, Zack J. Applications and validations of the MesoMap system in different climate regimes . paper presented at Windpower 2001, Am. Wind Energy Assoc., Washington D C, 2001.
[9] Warner T T, Kibler D F, Steinhart R L. Separate and coupled testing of meteorological and hydrological forecasting models for the Susquehanna River Basin in Pennsylvania [J]. J. Appl. Meteorol., 1991, 30: 1521-1533.
[10] Lau K H, Zhang Z F, Lam H Y, et al. Numerical simulation of a South China Sea typhoon Leo [J]. Meteorol. Atmos. Phys., 2002, 83: 147-161.
[11] Vaughan J, Lamb B, Frei C, et al. A numerical daily air quality forecast system for the Pacific Northwest [J]. Bull. Am. Meteorol. Soc., 2004, 85: 549-561.
[12] Chandrasekar A, Philbrick R, Clark B, et al. Evaluating the performance of a computationally efficient MM5/CALMET system for developing wind field inputs to air quality models [J]. Atmos. Environ., 2003, 37: 3267-3276.
[13] 中国气象局. 中国风能资源评价报告[M]. 北京: 气象出版社, 2006.
[14] Grell D J, Stauffer D R. A description of the fifth generation Penn State/NCAR mesoscale model (MM5) . http: //nldr.library.ucar.edu/collections/technotes/asset-000-000-000-214. pdf. 1995.
[15] Douglas S G, Kessler P C. User’s Guide to the Diagnostic Wind Model (Version 1. 0)[M]. Systems Applications Inc., San Rafael, Calif, CA. 1988.
