长江流域资源与环境 >> 2017, Vol. 26 >> Issue (11): 1795-.doi: 10.11870/cjlyzyyhj201711008

• 自然资源 • 上一篇    下一篇

利用CFSR数据开展海上风电场长年代风能资源评估

张双益, 胡非,王益群,张继立   

  1. (1. 中国科学院大气物理研究所大气边界层物理与大气化学国家重点实验室,北京 100029;2.中国科学院大学, 北京 100049;3.中国三峡新能源有限公司,北京 100053)
  • 出版日期:2017-11-20

APPLICATION OF CFSR DATA TO OFFSHORE WIND FARMS’ LONG TERM WIND ENERGY RESOURCE ASSESSMENT

ZHANG Shuangyi1,2,3, HU Fei1, WANG Yiqun3,ZHANG Jili3   

  1. (1. State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China; 2. University of Chinese Academy of Sciences, Beijing 100049, China; 3. China Three Gorges New Energy Co., Ltd, Beijing 100053, China
  • Online:2017-11-20

摘要: 开展长年代风能资源评估可为海上风电场的可行性研究和风险评估提供依据和支撑。创新性地引入了气候预测系统再分析(CFSR)数据,以江苏响水海上风电场为例开展了长年代风能资源评估,结果表明:CFSR数据10 m高度风速与海上气象塔10 m高度风速的平均偏差为 -0.2 m·s-1,均方根误差为 1.9 m·s-1;CFSR数据10 m高度风速与海上气象塔90 m高度风速的相关系数范围在0.359~0.619,相比气象站的相关系数提高了40%~90%;长年代订正得到海上气象塔90 m高度近30 a的风数据,多年平均风速为 6.9  m·s-1,标准差为 0.2 m·s-1(2.9%);测算出海上风电场近30年的等效满负荷小时数,多年平均值为 2 423 h,标准差为112 h(46%);评估出25 a一遇(海上风电场的寿命期)、10 a一遇、5 a一遇的最小年平均风速分别为6.6、6.7和 6.8 m·s-1,最小年等效满负荷小时数分别为 2 227、2 280 和 2 329 h。利用CFSR数据开展海上风电场长年代风能资源评估在技术上是可行的。

Abstract: Offshore wind power is an important resource in China’s thirteenth fiveyear plan of renewable energy development. Compared with nearshore wind farms, offshore wind farms have more complicated wind conditions, higher construction costs and lower risk bearing capacity. It is necessary to carry out long term wind energy resource assessment, which can provide offshore wind farms’ feasibility study and risk assessment. The NCEP (National Centers for Environmental Prediction)’s CFSR (Climate Forecast System Reanalysis) data have advantages of global coverage, high resolution and large marine data sources. In this study, the NCEP and CFSR data were applied to access the long term wind energy resource of the Xiangshui offshore wind farm in Jiangsu province. The results showed: (1) the mean deviation and rootmeansquareerror of the comparisons between CFSR and CFSR 10m height wind speed were -0.2 m·s-1 and 1.9 m·s-1, respectively.(2) The correlation coefficients between CFSR data’s 10m height wind speed and the offshore mast data’s 90 m height wind speed were 0.359-0.619, which were improved by 40%~90% compared to the meteorological station’s correlation coefficients. CFSR data could improve the long term correction method’s accuracy and correction result’s reliability. (3) The recent 30year wind data of the offshore mast’s 90 m height were obtained by application of CFSR data to long term correction, with the multiannual mean wind speed of 6.9 m·s-1and the standard deviation of 0.2 m·s-1 (2.9%). (4) The recent 30years equivalent full load hours of the offshore wind farm were calculated by the wind energy resource assessment software WAsP, with the multiyear mean value of 2 423 h and the standard deviation of 112 h (4.6%). (5) By the evaluation by the normal distribution model, the minimum yearly mean wind speeds in the 25 (the lifetime of offshore wind farms), 10 and 5 years period were 6.6, 6.7, and 6..8m·s-1, respectively; and the minimum equivalent full load hours were 2 227, 2 280, and 2 329 h, respectively. In conclusion, it is reasonable that applying the CFSR data on the offshore wind farms’ long term wind energy resource assessment. 

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