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