Two Neural Network Based Decentralized Controller Designs for Large Scale Power Systems

This paper presents two neural network (NN) based decentralized controller designs for large scale power systems’ generators, one is for the excitation control and the other is for the steam valve control. Though the control signals are calculated using local signals only, the transient and overall system stabilities can be guaranteed. NNs are used to approximate the unknown and/or imprecise dynamics of the local power system and the interconnection terms, thus the requirements for exact system parameters are released. Simulation studies with a three machine power system demonstrate the effectiveness of the proposed controller designs.

[1]  Q. Henry Wu,et al.  Decentralized nonlinear adaptive control for multimachine power systems via high-gain perturbation observer , 2004, IEEE Transactions on Circuits and Systems I: Regular Papers.

[2]  Kok Kiong Tan,et al.  Decentralized control design for large-scale systems with strong interconnections using neural networks , 2003, IEEE Trans. Autom. Control..

[3]  Qiang Lu,et al.  Nonlinear decentralized disturbance attenuation excitation control via new recursive design for multi-machine power systems , 2002, 2002 IEEE Power Engineering Society Winter Meeting. Conference Proceedings (Cat. No.02CH37309).

[4]  Shuzhi Sam Ge,et al.  Direct adaptive NN control of a class of nonlinear systems , 2002, IEEE Trans. Neural Networks.

[5]  Yi Guo,et al.  Nonlinear decentralized control of large-scale power systems , 2000, Autom..

[6]  Youyi Wang,et al.  Robust decentralized nonlinear controller design for multimachine power systems , 1997, Autom..

[7]  Zhihua Qu,et al.  Toward a globally robust decentralized control for large-scale power systems , 1997, IEEE Trans. Control. Syst. Technol..

[8]  Y. Ohsawa,et al.  Development of an advanced power system stabilizer using a strict linearization approach , 1996 .

[9]  Yoh-Han Pao,et al.  Stochastic choice of basis functions in adaptive function approximation and the functional-link net , 1995, IEEE Trans. Neural Networks.

[10]  Farshad Khorrami,et al.  Adaptive nonlinear excitation control of power systems with unknown interconnections , 1993, Proceedings of 32nd IEEE Conference on Decision and Control.

[11]  Nader Sadegh,et al.  A perceptron network for functional identification and control of nonlinear systems , 1993, IEEE Trans. Neural Networks.

[12]  H. Kaufman,et al.  Stabilizing a multimachine power system via decentralized feedback linearizing excitation control , 1993 .

[13]  Andrew R. Barron,et al.  Universal approximation bounds for superpositions of a sigmoidal function , 1993, IEEE Trans. Inf. Theory.