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
Link To Document :
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