Short-term Load Forecasting Based on 2-D Wavelet Transform

Ge Jia Xiao Xianyong

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Short-term Load Forecasting Based on 2-D Wavelet Transform

更新时间：2025-11-18

- Short-term Load Forecasting Based on 2-D Wavelet Transform
- Issue 3, Pages: 38-41+83(2007)
- 作者机构：
  
  1. 四川大学电气信息学院
  2. 四川大学电气信息学院四川成都610065
- 作者简介：
- 基金信息：
- DOI：
  CLC： TM715
- Published：2007
- 稿件说明：
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[1]葛嘉,肖先勇.基于二维小波变换的短期负荷预测[J].四川电力技术,2007(03):38-41+83.

Ge Jia Xiao Xianyong. Short-term Load Forecasting Based on 2-D Wavelet Transform[J]. 2007, (3): 38-41+83.
[1]葛嘉,肖先勇.基于二维小波变换的短期负荷预测[J].四川电力技术,2007(03):38-41+83. DOI：

Ge Jia Xiao Xianyong. Short-term Load Forecasting Based on 2-D Wavelet Transform[J]. 2007, (3): 38-41+83. DOI：

摘要

根据电力负荷的周期性与随机性

提出了基于二维小波变换和最小二乘支持向量机的电力系统短期负荷预测方法。首先构造负荷序列二维矩阵

利用二维小波变换将负荷矩阵分解为基荷低频、每天变化的高频、每个时刻变化的高频、随机干扰四个分量

根据重构后负荷分量的特点

构造不同的最小二乘支持向量机模型进行预测;最后将预测后的数据进行叠加得到预测结果。实际预测结果表明该方法具有较高的预测精度和较强的适应能力。

Abstract

According to randomness and periodicity of power load

a new method for short-term load forecasting is proposed based on 2-D wavelet transform and least square support vector machine（LS-SVM）.At first

the load series matrix is decomposed into 4 components based on 2-D wavelet transform

then every component is reconstructed and according to the characteristics of the series

the different LS-SVM models are established to forecast load

finally the ultimate forecasting result is obtained after the forecasted load is superposed.The real forecasting result shows that the proposed method is much more accurate and validate

and it also can decrease the risk of the forecasting

so it is an effective method for short-term load forecasting.

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四川大学电气信息学院

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