DocumentCode :
2830442
Title :
Power system harmonics prediction with an artificial neural network
Author :
Mori, Hiroyuki ; Suga, Shinji
Author_Institution :
Dept. of Electr. Eng., Meiji Univ., Kawasaki, Japan
fYear :
1991
fDate :
11-14 Jun 1991
Firstpage :
1129
Abstract :
Describe an artificial neural net (ANN) based approach to prediction of power system harmonic voltages. The effectiveness of recurrent neural networks is examined. Recurrent neural networks have the advantage of being able to consider the dynamics of a time series, unlike the conventional feedforward ANN. Four recurrent neural networks are applied to prediction of the fifth harmonic voltage. A comparison is made of the four recurrent network models from the standpoint of accuracy and computational efforts
Keywords :
harmonics; neural nets; power system analysis computing; accuracy; artificial neural network; computational efforts; network models; power system harmonic voltages; recurrent neural networks; time series; Artificial neural networks; Backpropagation; Computer networks; Load forecasting; Pattern recognition; Power system dynamics; Power system harmonics; Power system modeling; Recurrent neural networks; Voltage;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Circuits and Systems, 1991., IEEE International Sympoisum on
Print_ISBN :
0-7803-0050-5
Type :
conf
DOI :
10.1109/ISCAS.1991.176565
Filename :
176565
Link To Document :
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