Research of short-term load forecasting based on combined grey neural network and phase space reconstruction

Author

Wang, Shuo-he ; Hao, Rui-lin ; Chang, Yu-jian ; Zhao, Yao

Author_Institution

Dept. of Electr. & Electron Eng., Shijiazhuang Railway Inst., Shijiazhuang, China

Volume

2

fYear

2009

fDate

12-15 July 2009

Firstpage

1194

Lastpage

1199

Abstract

According to the characteristics of grey theory, G-P algorithm of phase space reconstruction and artificial neural network (ANN), a combined algorithm (G-G-NN) is proposed. The original time series is transformed by accumulated generating of grey prediction and G-P algorithm of phase space reconstruction. When a regular time series phase space is generated, neural network is adopted to forecast. The practical example indicated that the algorithm is verified.

Keywords

grey systems; load forecasting; neural nets; power system analysis computing; G-P algorithm; artificial neural network; grey neural network; grey theory; phase space reconstruction; short-term load forecasting; Artificial neural networks; Clustering algorithms; Cybernetics; Load forecasting; Machine learning; Neural networks; Power system modeling; Prediction algorithms; Predictive models; Steel; Electric power systems; G-G-NN algorithm; G-P algorithm; Grey theory; Neural network; Short-term load forecasting;

fLanguage

English

Publisher

ieee

Conference_Titel

Machine Learning and Cybernetics, 2009 International Conference on

Conference_Location

Baoding

Print_ISBN

978-1-4244-3702-3

Electronic_ISBN

978-1-4244-3703-0

Type

conf

DOI

10.1109/ICMLC.2009.5212444

Filename

5212444