A New Short-Term Load Forecasting Model of Power System Based on HHT and ANN

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NETL

外文摘要：Aiming to the disadvantages of short-term load forecasting with HHT such as mode mixing and random component， a new short-term load forecasting model based on HHT and ANN is proposed。 The first order difference algorithm is adopted to eliminate mode mixing。 The random component is forecast with different methods including BP， RBF， SVM， linear and ANN combination。 Other components can be forecast with proper method。 The simulation results show that the higher accuracy of short-term load forecasting can be obtained。

外文关键词：

short-term load forecastingHHTANNcombination model

作者：

Zhigang Liu、Weili Bai、Gang Chen

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作者单位：

School of Elec. Eng., Southwest Jiaotong University, Chengdu 610031, Sichuan, China

会议名称：

ISNN 2010;International symposium on neural networks

会议地点：

Shanghai(CN);Shanghai(CN)

会议母体文献：

Advances in neural networks - ISNN 2010

页码：

p.448-454

出版时间：

2010