DocumentCode
1948121
Title
Load modelling in commercial power systems using neural networks
Author
Song, Y.H. ; Dang, D.Y.
Author_Institution
Sch. of Electr. Eng. & Electron., Liverpool John Moores Univ., UK
fYear
1994
fDate
1-5 May 1994
Firstpage
1
Lastpage
6
Abstract
Power system load modelling is of vital importance in power flow, transient stability and voltage stability studies. It is, however, a very difficult task because load representation is qualitatively different in many aspects. Conventional approaches employ mathematical models to represent the steady and dynamic characteristics of various loads. With the advent of neural computing, attempts have constantly been made to address this problem by using this new technique. This paper discusses the applications of neural networks to the representation of the aggregation of busbar loads which are comprised of mixed but known composition
Keywords
busbars; digital simulation; load flow; neural nets; power system analysis computing; power system stability; power system transients; applications; busbar; computer simulation; load modelling; load representation; mathematical models; neural networks; power flow; power systems; transient stability; voltage stability; Industrial power systems; Load flow; Load modeling; Mathematical model; Neural networks; Power system dynamics; Power system modeling; Power system stability; Power system transients; Voltage;
fLanguage
English
Publisher
ieee
Conference_Titel
Industrial and Commercial Power Systems Technical Conference, 1994. Conference Record, Papers Presented at the 1994 Annual Meeting, 1994 IEEE
Conference_Location
Irvine, CA
Print_ISBN
0-7803-1877-3
Type
conf
DOI
10.1109/ICPS.1994.303546
Filename
303546
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