DocumentCode
3517579
Title
Power load forecasting based on elman neural network
Author
Heng, Zhang ; Huanqi, Tao
Author_Institution
Coll. of Electron. & Inf. Eng., Wuhan Univ. of Sci. & Eng., Wuhan, China
Volume
4
fYear
2009
fDate
8-9 Aug. 2009
Firstpage
374
Lastpage
376
Abstract
The article forecasts the power load with Elman neural network. First of all, it gives the basic principle of Elman neural network, and then it determines the structure parameters, transfer function and training times of model, normalizes the data. It gets a good result with forecasting actual history data of a certain electric network; it shows that forecasting power load with Elman neural network is available.
Keywords
load forecasting; neural nets; power engineering computing; transfer functions; Elman neural network; power load forecasting; transfer function; Economic forecasting; Educational institutions; Load forecasting; Neural networks; Neurons; Nonlinear dynamical systems; Power engineering and energy; Power generation economics; Recurrent neural networks; Transfer functions; Elman neural network; forecast; forecast accuracy; normalization; power load;
fLanguage
English
Publisher
ieee
Conference_Titel
Computing, Communication, Control, and Management, 2009. CCCM 2009. ISECS International Colloquium on
Conference_Location
Sanya
Print_ISBN
978-1-4244-4247-8
Type
conf
DOI
10.1109/CCCM.2009.5270429
Filename
5270429
Link To Document