| 基于最小二乘支持向量机的风速预测模型 |
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| 引用本文： | 曾杰,张华. 基于最小二乘支持向量机的风速预测模型[J]. 电网技术, 2009, 33(18): 144-147 |
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| 作者姓名： | 曾杰 张华 |
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| 作者单位： | 华北电力大学,可再生能源学院,北京市,昌平区,102206;华北电力大学,可再生能源学院,北京市,昌平区,102206 |
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| 摘 要： | 风速具有较大的随机性,预测的准确度不高。针对这种现象,基于最小二乘支持向量机(least squares support vector machine,LS-SVM)理论,结合某风电场实测风速数据,建立了最小二乘支持向量机风速预测模型。对该风电场的风速进行了提前1h的预测,其预测的平均绝对百分比误差仅为8.55%,预测效果比较理想。同时将文中的风速预测模型与神经网络理论、支持向量机(support vector machine,SVM)理论建立的风速预测模型进行了比较。仿真结果表明,文中所提模型在预测精度和运算速度上皆优于其他模型。
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| 关 键 词： | 风速预测 最小二乘支持向量机(LS-SVM) 风电场 支持向量机(SVM) 神经网络 |
A Wind Speed Forecasting Model Based on Least Squares Support Vector Machine |
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| ZENG Jie,ZHANG Hua. A Wind Speed Forecasting Model Based on Least Squares Support Vector Machine[J]. Power System Technology, 2009, 33(18): 144-147 |
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| Authors: | ZENG Jie ZHANG Hua |
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| Affiliation: | ZENG Jie,ZHANG Hua (School of Renewable Energy,North China Electric Power University,Changping District,Beijing 102206,China) |
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| Abstract: | Due to its strong randomness,it is very difficult to predict wind speed accurately. To solve this problem,using least squares support vector machine (LS-SVM) and based on actual wind speed data measured in a certain wind farm,a wind speed predicting model based on LS-SVM is built; the one hour-ahead wind speed of this wind farm is predicted by the proposed model,and a satisfied prediction result that the mean average percentage error of the predicted wind speed is only 8.55% is obtained. The proposed wind s... |
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| Keywords: | wind speed forecasting least squares support vector machine (LS-SVM) wind farm support vector machine (SVM) neural network |
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