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基于小波分解和最小二乘支持向量机的短期风速预测
引用本文:王晓兰,王明伟.基于小波分解和最小二乘支持向量机的短期风速预测[J].电网技术,2010(1).
作者姓名:王晓兰  王明伟
作者单位:兰州理工大学电气工程与信息工程学院;
基金项目:甘肃省自然科学基金资助项目(0710RJZA054)
摘    要:短期风速预测对并网风力发电系统的运行有重要意义。对风速进行较准确地预测,可以有效减轻或避免风电场对电力系统的不利影响,同时提高风电场在电力市场中的竞争能力。简述了短期风速预测的价值和方法,提出了基于小波分解(wavelet decomposition,WD)和最小二乘支持向量机(least square support vector machine,LS-SVM)的短期风速预测方法,分别以香港和河西走廊地区风电场为例,建立了上述2个地区风速预测的WD-LSSVM模型,根据上述地区的数据进行实例验证,结果表明文中的方法显著提高了超前一步预测的精度。

关 键 词:风速预测  风力发电  风电场  小波分解  最小二乘支持向量机  

Short-Term Wind Speed Forecasting Based on Wavelet Decomposition and Least Square Support Vector Machine
WANG Xiao-lan,WANG Ming-wei.Short-Term Wind Speed Forecasting Based on Wavelet Decomposition and Least Square Support Vector Machine[J].Power System Technology,2010(1).
Authors:WANG Xiao-lan  WANG Ming-wei
Affiliation:College of Electrical Engineering and Information Engineering;Lanzhou University of Technology;Lanzhou 730050;Gansu Province;China
Abstract:Short-term wind speed forecasting is of significance for the operation of grid-connected wind power generation systems.A more accurate wind speed forecasting can effectively reduce or avoid the adverse effect of wind farm on power grid,meanwhile strengthens competition ability of wind farm in electricity market.In this paper the value and methods of wind speed forecasting are briefly introduced,and a short-term wind speed forecasting method based on wavelet decomposition(WD) and least square support vector ...
Keywords:wind speed forecasting  wind power generation  wind farm  wavelet decomposition  least square support vector machine  
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