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中尺度模式风电场风速短期预报能力研究
引用本文:张宇,郭振海,林一骅,迟德中.中尺度模式风电场风速短期预报能力研究[J].大气科学,2013,37(4):955-962.
作者姓名:张宇  郭振海  林一骅  迟德中
作者单位:1.中国科学院大气物理研究所大气科学和地球流体力学数值模拟国家重点实验室,北京100029;中国科学院大学研究生院,北京100049
基金项目:中国科学院战略性先导科技专项项目XDA05110300
摘    要:本文利用内蒙古乌兰察布风电场2009 年观测记录和WRF 数值模式预报,研究了中尺度数值天气模式对风电场风速的短期预报能力。研究表明:不同数值模式参数化方案的预报能力没有实质性的区别,对于不同时效的风场预报各种方案的预报能力不尽相同。在天气演变较为剧烈时,模式预报技巧相对较差。风电场周边主要天气系统对预报准确度有很大影响。就乌兰察布风电场而言,WRF 模式2009 年日平均预报相对误差仅为11.78%,且误差大于20%的日数占研究总天数不超过15%,具有较高的预报技巧。当蒙古气旋、东北气旋剧烈发展或风速迅速减小时风速的预报误差较大。

关 键 词:风力发电    短期风速预报    中尺度模式    天气分析
收稿时间:2012/6/13 0:00:00
修稿时间:2012/11/22 0:00:00

Predictive Capacity of Mesoscale Model for Short-Range Wind Speed Forecasting at Wind Power Farm
ZHANG Yu,GUO Zhenhai,LIN Yihua and CHI Dezhong.Predictive Capacity of Mesoscale Model for Short-Range Wind Speed Forecasting at Wind Power Farm[J].Chinese Journal of Atmospheric Sciences,2013,37(4):955-962.
Authors:ZHANG Yu  GUO Zhenhai  LIN Yihua and CHI Dezhong
Affiliation:1.State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029;Graduate University of Chinese Academy of Sciences, Beijing 1000492.State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 1000293.School of Mathematics and Statistics, Lanzhou University, Lanzhou 730000
Abstract:The predictive capacity of a mesoscale model for short-range wind speed forecasting at a wind power farm is investigated. The results of the Weather Research and Forecasting Model (WRF) are compared and analyzed in this paper and also compared with observation data at a wind power farm in Ulan Qab. The research shows that although the model parameterization schemes' forecasting ability varies with time, the schemes show no essential difference. The forecast level is relatively low when the weather is developing acutely. The synoptic background is the main contributor to the model's predictive capacity. At this wind farm, the daily mean forecast relative error of the WRF forecast with respect to the observation is only 11.78% in 2009, and the number of days for which the error is greater than 20% does not exceed 15%. The forecast error predominantly appears when the wind speed weakens rapidly or a Mongolian cyclone or Northeast cyclone undergoes dramatic evolution.
Keywords:Wind power  Short-range wind speed forecast  Mesoscale model  Synoptic analysis
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