DocumentCode :
493660
Title :
Medium-Long Power Load Forecasting Based on Improved Grey BP Model
Author :
Li, Xiaoxia ; Zhang, Peijun
Author_Institution :
Dept. of Inf. & Electron. Eng.[1], Hebei Univ. of Eng., Handan
Volume :
2
fYear :
2009
fDate :
7-8 March 2009
Firstpage :
366
Lastpage :
368
Abstract :
The power load forecasting precision being influenced by many factors, the traditional forecasting tools are not very taking the role. In fact, BP network has the characteristics of the applicable and self-learning, and grey method has the growth characteristics,this paper used the correcting coefficient to improved the grey method, so the grey BP network method can better reflect the increasing and non-linearity character than traditional grey BP method. The minimal variance method was used as the making of combination weight, through the advantages of the two methods, we can meet the high precision for the forecasting, and the whole forecasting results have greatly improved to conventional methods, above all, this method can be better using in medium and long term power load forecasting.
Keywords :
backpropagation; grey systems; load forecasting; neural nets; power engineering computing; grey BP neural network model; medium-long power load forecasting; minimal variance method; power system planning; Computer science education; Economic forecasting; Educational technology; Load forecasting; Neural networks; Power engineering and energy; Power engineering education; Power generation economics; Power supplies; Predictive models; BP network; combined weight; grey model; medium-long; power load;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Education Technology and Computer Science, 2009. ETCS '09. First International Workshop on
Conference_Location :
Wuhan, Hubei
Print_ISBN :
978-1-4244-3581-4
Type :
conf
DOI :
10.1109/ETCS.2009.343
Filename :
4959057
Link To Document :
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