DocumentCode :
2755130
Title :
Application of Elman Neural Network and MATLAB to Load Forecasting
Author :
Ren Lina ; Liu Yanxin ; Rui Zhiyuan ; Li Haiyan ; Feng Ruicheng
Author_Institution :
Key Lab. of Digital Manuf. Technol. & Applic., Lanzhou Univ. of Tech., Lanzhou, China
Volume :
1
fYear :
2009
fDate :
25-26 July 2009
Firstpage :
55
Lastpage :
59
Abstract :
In order to improve the load-forecast precision and availability of power system, a method based on Elman neural network and MATLAB is presented to create a load forecast model, which according to the Elman neural network model having the characteristics of approach to arbitrary nonlinear functions and having the ability of reflecting the dynamic behavior of the system and for the practicability and high efficiency of using neural network tool-box in MATLAB to program. Then using actual load data to train the model, the emulation results show that the model is of quickly convergence speed and high forecasting precision, which can meet the needs of running and scheduling in power system, and using neural network tool-box in MATLAB to program can make the worker won free of elaborate program and make the working efficiency improved effectively. The example is of proof that the method is feasible and effective.
Keywords :
load forecasting; mathematics computing; neural nets; power system analysis computing; Elman neural network; Matlab; load forecasting; power system; Availability; Load forecasting; Load modeling; MATLAB; Mathematical model; Neural networks; Nonlinear dynamical systems; Power system dynamics; Power system modeling; Predictive models; Elman neural network; MATLAB; electric load; forecast model;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Technology and Computer Science, 2009. ITCS 2009. International Conference on
Conference_Location :
Kiev
Print_ISBN :
978-0-7695-3688-0
Type :
conf
DOI :
10.1109/ITCS.2009.20
Filename :
5190016
Link To Document :
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