DocumentCode :
1948794
Title :
Load characteristics identification using artificial neural network and transient stability analysis
Author :
Kim, Tae-Eung ; Ji, Pyeong-Shik ; Lee, Jong-Pil ; Nam, Sang-Cheon ; Kim, Jung-Hmn ; Lim, Jae-Yoon
Author_Institution :
Dept. of Electr. Eng., Chung-Buk Nat. Univ., Cheongju, South Korea
Volume :
1
fYear :
1998
fDate :
3-5 Mar 1998
Firstpage :
329
Abstract :
The modeling of load characteristics is a difficult problem because of uncertainty of the load. This research uses artificial neural networks which can approximate the nonlinear problem to represent load characteristics. After the selection of a typical load, active and reactive power for the variation of voltage and frequency is obtained from experiments. On the basis of obtained data, the load model represented by a neural network is acquired Then the propriety is submitted by case studies
Keywords :
load (electric); neural nets; parameter estimation; power system analysis computing; power system stability; power system transients; reactive power; active power; artificial neural network; frequency variation; load characteristics identification; load characteristics modelling; load uncertainty; nonlinear problem; reactive power; transient stability analysis; voltage variation; Artificial neural networks; Equations; Frequency; Load modeling; Mathematical model; Power system modeling; Power system transients; Stability analysis; Transient analysis; Voltage;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Energy Management and Power Delivery, 1998. Proceedings of EMPD '98. 1998 International Conference on
Print_ISBN :
0-7803-4495-2
Type :
conf
DOI :
10.1109/EMPD.1998.705547
Filename :
705547
Link To Document :
بازگشت