Title :
A novel power system stabilizer based on neural network inverse system
Author :
Hu, Zhijian ; Liang, Youwei ; Chen, Yunping ; Zhang, Chengxue
Author_Institution :
Coll. of Electr. Eng., Wuhan Univ., China
Abstract :
A novel power system stabilizer (PSS) based on the neural networks α-th order inverse system (called NNIPSS) is proposed in this paper. The reversibility of excitation system with PSS in power systems is proved firstly. Then selecting the power angle as the output variable, the control structure of the NNIPSS is given and the sample selection and training methods of the neural network inverse system are described in detail. In order to improve the dynamics performance and robustness of the pseudo-linear system, a fuzzy-PID controller is employed. Simulations of one machine infinite bus system show the effectiveness of the NNIPSS.
Keywords :
data acquisition; fuzzy control; learning (artificial intelligence); neural nets; power system control; power system stability; three-term control; α-th order inverse system; data acquisition; excitation system reversibility; fuzzy-PID controller; infinite bus system; neural network inverse system; power system stabilizer; pseudo-linear system; sample selection method; Control systems; Control theory; Neural networks; Power system analysis computing; Power system control; Power system dynamics; Power system modeling; Power system simulation; Power system stability; Power systems;
Conference_Titel :
Information Acquisition, 2004. Proceedings. International Conference on
Print_ISBN :
0-7803-8629-9
DOI :
10.1109/ICIA.2004.1373423
