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风电场超短期风速预测方法对比
引用本文:伍见军,王咏薇.风电场超短期风速预测方法对比[J].科学技术与工程,2013,13(11):2965-2969.
作者姓名:伍见军  王咏薇
作者单位:南京信息工程大学大气物理学院,南京信息工程大学大气环境中心
基金项目:江苏省科技支撑计划(No:BE2010200);江苏高校优势学科建设工程(PAPD);长江学者和创新团队发展计划资助
摘    要:以沿海及山地复杂地形条件下的风电场为例,采用为期10 d的风电场测风塔实测风速资料,对比了两种预测方法在时效为4 h的超短期风速预测中的性能。其一为采用WRF数值模式预报的物理方法,其二为BP神经网络的统计方法;并探讨了两种风速预测方法的实用价值及意义。结果表明,与物理模拟方法相比,统计方法在4 h的超短期风速预测中,无论是预测准确性及计算效率都有一定的优势。

关 键 词:复杂地形条件  风电场风速预测  统计预报  物理模拟  方法对比
收稿时间:2012/12/11 0:00:00
修稿时间:2012/12/11 0:00:00

A Comparison of Very Short Term Wind Prediction by Different Methods
wu jian jun and wang yong wei.A Comparison of Very Short Term Wind Prediction by Different Methods[J].Science Technology and Engineering,2013,13(11):2965-2969.
Authors:wu jian jun and wang yong wei
Institution:4(School of Atmospheric physics1,Center on Atmospheric Environment2,Nanjing University of Information Science and Technology, Nanjing 210044,P.R.China;College of Electrical Engineering,Southeast University3,Nanjing 211100,P.R.China; Beijing Sifang Automation Co.Ltd4,Beijing 100085,P.R.China)
Abstract:The paper took wind farms at complex terrain condition like coastal areas and mountainous areas for instances to contrast the results of two prediction methods with ten-days observations from wind-towers, the one method was WRF simulation and the other was BP neural network statistical prediction. The accuracy of wind prediction in 4 hours term between two methods was analyzed. The practical value and significance of the two methods were also discussed. Results show, the statistical prediction had obvious advantages in accuracy and computation efficiency in 4 hours term compared with the physical simulation.
Keywords:complex terrain wind speed prediction statistical prediction physical simulation methods comparison
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