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基于SVM的时间序列短期风速预测
引用本文:鲍永胜,吴振升.基于SVM的时间序列短期风速预测[J].中国电力,2011,44(9):61-64.
作者姓名:鲍永胜  吴振升
作者单位:北京交通大学电气工程学院,北京,100044
摘    要:短期风速预测对风力发电系统的并网运行具有重要意义。对风速进行较准确预测,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。介绍了支持向量机(SVM)理论的新应用,讨论支持向量机理论用于风速预测的具体过程;建立基于支持向量机风电场短期风速预测模型,此模型仅以历史风速数据为输入,简单、高效,不需要其他额外的气象数据。与改进模糊层次分析法的组合模型、ARMA-ARCH模型、EMD-ARMA模型、双自回归滑动平均模型的预测结果进行比较,证实支持向量机理论的应用是有效的,可以用于风速的短期预测和发电量预测。

关 键 词:短期风速预测  支持向量机(SVM)  风电场

Short-term wind speed forecasting based on SVM time-series method
BAO Yong-sheng,WU Zhen-sheng.Short-term wind speed forecasting based on SVM time-series method[J].Electric Power,2011,44(9):61-64.
Authors:BAO Yong-sheng  WU Zhen-sheng
Affiliation:BAO Yong-sheng,WU Zhen-sheng(School of Electrical Engineering,Beijing Jiaotong University,Beijing 100044,China)
Abstract:Short-term wind speed forecasting is of significance for the operation of grid-connected wind power generation systems.An accurate wind speed forecasting can effectively reduce or avoid the adverse effect of wind farm on power grid and strengthen competition ability of wind farm in electricity market.A new application of the Support Vector Machine(SVM) theory is introduced.The detailed process for SVM usage in wind forecast process is discussed.A SVM wind speed forecast model for wind farm is founded.This m...
Keywords:short-term wind speed forecasting  support vector machine(SVM)  wind farm  
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