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基于小波变换的系统边际电价分析与预测
引用本文:唐明,马光文,徐刚.基于小波变换的系统边际电价分析与预测[J].四川大学学报(工程科学版),2007,39(4):12-15.
作者姓名:唐明  马光文  徐刚
作者单位:四川大学,水利水电学院,四川,成都,610065
摘    要:摘要:基于小波变换的系统边际电价(System Marginal Price,SMP)数据分析,根据系统边际电价的特点,建立用于系统边际电价预测的模型。利用小波变换时频局部化功能,将原电价时间序列分解成不同的尺度,对不同尺度上的子序列分别采用人工神经网络和AR模型进行预测,最后将不同尺度预测结果通过小波重构还原,得到系统边际电价预测结果。实例验证表明预测模型能有效提高预测精度,可用于系统边际电价预测。

关 键 词:系统边际电价  预测  小波分析  人工神经网络
文章编号:1009-3087(2007)04-0012-04
收稿时间:2006/11/30 0:00:00
修稿时间:2006-11-30

Analysis and Forecasting SMP Using Wavelet Transform
TANG Ming,MA Guang-wen,XU Gang.Analysis and Forecasting SMP Using Wavelet Transform[J].Journal of Sichuan University (Engineering Science Edition),2007,39(4):12-15.
Authors:TANG Ming  MA Guang-wen  XU Gang
Affiliation:School of Water Resources and Hydropower, Sichuan Univ., Chengdu 610065, China;School of Water Resources and Hydropower, Sichuan Univ., Chengdu 610065, China;School of Water Resources and Hydropower, Sichuan Univ., Chengdu 610065, China
Abstract:Using wavelet transform,the characteristics of periodicity SMP time series have been probed.According to the characteristics of SMP,this paper presents combined forecast method based on wavelet transform.The non-stationary time series of SMP is decomposed into several detailed stationary time series and a smoothed non-stationary time series according to the principle of wavelet decomposition.The stationary time series is simulated by using AR(p) method and the non-stationary series is simulated by using artificial neural network model.The comparison shows that the error of the simulation adopting this method is smaller than that by using auto-regressive method.
Keywords:SMP  forecast  wavelet transform  ANN
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