DocumentCode
3147268
Title
Approximations of power system dynamic load characteristics by artificial neural networks
Author
Thomas, Robert J. ; Ku, Bih-Yuan
Author_Institution
Sch. of Electr. Eng., Cornell Univ., Ithaca, NY, USA
fYear
1991
fDate
23-26 Jul 1991
Firstpage
178
Lastpage
182
Abstract
The static and dynamic characteristics of power system loads are critical to obtaining quality operating point predictions or stability calculations. The composite behavior of components at load buses are usually too complicated to be expressed in a simple form. Based on the approximation capability of artificial neural networks the authors explore the possibility of using neural networks to emulate load behaviours. The results verify the potential of load representation by neural networks
Keywords
load (electric); neural nets; power system analysis computing; artificial neural networks; load buses; power system dynamic load characteristics; quality operating point predictions; stability calculations; Artificial neural networks; Frequency; Impedance; Load modeling; Neural networks; Power system dynamics; Power system modeling; Power system planning; Power system stability; Voltage;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks to Power Systems, 1991., Proceedings of the First International Forum on Applications of
Conference_Location
Seattle, WA
Print_ISBN
0-7803-0065-3
Type
conf
DOI
10.1109/ANN.1991.213482
Filename
213482
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