[1]蒋建东,张豪杰,王静.基于HHT的电力负荷组合预测应用[J].郑州大学学报(工学版),2015,36(04):1-5.[doi:10.3969/ j. issn.1671 - 6833.2015.04.001]
　JIANG Jian-dong,ZHANG Hao-jie,WANG Jing.Research and Application of HHT-Based Power Load Combination Forecasting[J].Journal of Zhengzhou University (Engineering Science),2015,36(04):1-5.[doi:10.3969/ j. issn.1671 - 6833.2015.04.001]
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基于HHT的电力负荷组合预测应用()
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《郑州大学学报(工学版)》[ISSN:1671-6833/CN:41-1339/T]

卷:
36
期数:
2015年04期
页码:
1-5
栏目:
出版日期:
2015-08-31

文章信息/Info

Title:
Research and Application of HHT-Based Power Load Combination Forecasting
作者:
蒋建东; 张豪杰; 王静
1.郑州大学电气工程学院，河南郑州450001;2.济源供电公司，河南济源459000
Author(s):
JIANG Jian-dong1 ; ZHANG Hao-jie1 ; WANG Jing2
1.School of Electrical Engineering,Zhengahou University , Zhengzhou 450001 , Chima; 2.Jiyuan City Power Supply Company,Jiyuan 459000 , China
关键词:
负荷预测; 影响因素; 希尔伯特黄变换; 神经网络; 时间序列
Keywords:
load forecasting; influencing factor; Hilbert Huang transform; neural network ;  time series
DOI:
10.3969/ j. issn.1671 - 6833.2015.04.001
文献标志码:
A
摘要:
为了进一步提高电力负荷预测精度,在对电力负荷影响因素分析的基础上,提出了一种基于HHT的负荷组合预测模型.该模型利用EMD算法将原始负荷序列分解,得到不同频率的平稳子序列，子序列比原始序列更具可预测性.根据不同频率的子序列特点选取RBF神经网络、BP神经网络和时间序列模型分别预测,同时考虑温度对负荷的影响,得到新的组合模型.算例表明,该模型能有效提高电力负荷预测精度.
Abstract:
To further improve the accuracy of power load forecasting，on the basis of the analysis of affectingfactors of power load, a combination prediction model based on HHT is proposed. This model uses EMD algo-rithm to decompose the original load sequence. Thus， a stationary sequence of different frequencies，which ismore predictable than the original load sequence，can be obtained. Based on the components of different fre-quencies，according to the characteristics of the different frequency of subsequence ，the RBF neural network ,BP neural network and time series model are selected to forecast while considering the influence of temperatureon the load. Then，a new combined model can be achieved. The experiment shows that the proposed modelcan effectively improve the accuracy of load forecasting.

参考文献/References:

[1]康重庆,夏清,刘梅.电力系统负荷预测[M ].北京:中国电力出版社,2007 :2 -63.

[2]白玮莉,刘志刚,彭权威,等.基于HHT和神经网络组合的负荷预测模型研究[J].电力系统保护与控制,2009 ,37( 19) :31 - 35.
[3]李媛媛,牛东晓,乞建勋.基于经验模式分解的电力负荷混合预测方法[J].电网技术,2008,32 ( 8 ) :58-62.

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