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Adaptive conventional power system stabilizer based on artificial neural network

Conference ·
OSTI ID:474576
 [1];  [2];  [3]
  1. Indian Inst. of Tech., New Delhi (India). Dept. of Electrical Engineering
  2. Bharat Heavy Electricals Ltd., New Delhi (India)
  3. Tata Hydro, Bombay (India)

This paper deals with an artificial neural network (ANN) based adaptive conventional power system stabilizer (PSS). The ANN comprises an input layer, a hidden layer and an output layer. The input vector to the ANN comprises real power (P) and reactive power (Q), while the output vector comprises optimum PSS parameters. A systematic approach for generating training set covering wide range of operating conditions, is presented. The ANN has been trained using back-propagation training algorithm. Investigations reveal that the dynamic performance of ANN based adaptive conventional PSS is quite insensitive to wide variations in loading conditions.

OSTI ID:
474576
Report Number(s):
CONF-9601119--; ISBN 0-7803-2795-0
Country of Publication:
United States
Language:
English

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