Research and Application of HHT-Based Power Load Combination Forecasting
[1]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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Journal of Zhengzhou University (Engineering Science)[ISSN
1671-6833/CN
41-1339/T] Volume:
36
Number of periods:
2015 04
Page number:
1-5
Column:
Public date:
2015-08-31
- Title:
- Research and Application of HHT-Based Power Load Combination Forecasting
- Keywords:
- load forecasting; influencing factor; Hilbert Huang transform; neural network ; time series
- CLC:
- -
- 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.
- 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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