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Tuning of power system stabilizers using an artificial neural network

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2 Author(s)
Hsu, Yuan-Yih ; Dept. of Electr. Eng., Nat. Taiwan Univ., Taipei, Taiwan ; Chao-Rong Chen

A new approach using an artificial neural network is proposed to adapt power system stabilizer (PSS) parameters in real time. A pair of online measurements i.e., generator real-power output and power factor which are representative of the generator's operating condition, are chosen as the input signals to the neural net. The outputs of the neural net are the desired PSS parameters. The neural net, once trained by a set of input-output patterns in the training set, can yield proper PSS parameters under any generator loading condition. Digital simulations of a synchronous machine subject to a major disturbance of a three-phase fault under different operating conditions are performed to demonstrate the effectiveness of the proposed neural network

Published in:

Energy Conversion, IEEE Transactions on  (Volume:6 ,  Issue: 4 )

Date of Publication:

Dec 1991

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