DocumentCode :
1861426
Title :
Load forecasting based on intelligence information processing
Author :
Hua, Zheng ; Li, Xie ; Li-zi, Zhang
Author_Institution :
Inst. of Electr. Market Res., North China Electr. Power Univ., Beijing
fYear :
2005
fDate :
Nov. 29 2005-Dec. 2 2005
Firstpage :
1
Lastpage :
426
Abstract :
In electricity market, it is widely accepted that short-term load forecast is a key problem of market operation. In this paper, a novel model for load forecasting based on intelligence information processing is presented. Here, we make full use of the excellent property reconstruction ability of independent component analysis, which is a new intelligence information processing technology for separating signals and making them independent mutually, and presents STLF model based independent property reconstruction. The load properties of different kinds are restructured to enhance its representation ability and simplifying STLF modeling by ANN. After neural network is trained by new properties with lower dimension, STLF model is built. Finally, the real load data of spot market in New England is applied to demonstrate the validity of the proposed approach
Keywords :
independent component analysis; load forecasting; neural nets; power engineering computing; power markets; New England; electricity market; independent component analysis; intelligence information processing; neural network; short-term load forecast; spot market; Artificial neural networks; Electricity supply industry; Independent component analysis; Information processing; Intelligent networks; Load forecasting; Load modeling; Neural networks; Predictive models; Signal processing; Independent Component Analysis; Intelligence Information Processing; Load Forecasting; Neural Network;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Power Engineering Conference, 2005. IPEC 2005. The 7th International
Conference_Location :
Singapore
Print_ISBN :
981-05-5702-7
Type :
conf
DOI :
10.1109/IPEC.2005.206946
Filename :
1627235
Link To Document :
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