Application of ANN technique based on μ-synthesis to load frequency control of interconnected power system

A nonlinear artificial neural networks (ANN) controller based on μ-synthesis for solution the load frequency control (LFC) problem is proposed in this paper. Power systems such as other industrial plants subject to some uncertainties and disturbances due to multivariable operating conditions and load changes. In order to take large modeling errors and minimize the effects of area load disturbances, the idea of μ-synthesis theory is being used for training ANN based LFC controller. This newly developed design strategy combines advantage of the ANN and μ-synthesis control techniques to achieve the desired level of robust performance for all admissible uncertainties and leads to a flexible controller with relatively simple structure, which can be useful in the real world complex power system. A two-area power system is considered as a test system to demonstrate the effectiveness of the proposed method in comparison with the conventional PI and μ-based robust controllers under various operating conditions and load changes. The simulation results show that the proposed ANN based controller achieves good robust performance even in the presence of generation rate constraints (GRC) and is superior to the other controllers.

[1]  Andrew Packard,et al.  The complex structured singular value , 1993, Autom..

[2]  C. T. Pan,et al.  An Adaptive Controller for Power System Load-Frequency Control , 1989, IEEE Power Engineering Review.

[3]  Yasunori Mitani,et al.  Robust load frequency control by solid-state phase shifter based on /spl Hscr//sup /spl infin// control design , 1999, IEEE Power Engineering Society. 1999 Winter Meeting (Cat. No.99CH36233).

[4]  Shinichi Iwamoto,et al.  Design of load frequency control based on /spl mu/-synthesis , 2002, IEEE/PES Transmission and Distribution Conference and Exhibition.

[5]  Gary J. Balas,et al.  μ-analysis and synthesis toolbox: for use with Matlab , 1994 .

[6]  J. P. Chretien,et al.  μ synthesis by D - K iterations with constant scaling , 1993, 1993 American Control Conference.

[7]  Simon Haykin,et al.  Neural Networks: A Comprehensive Foundation , 1998 .

[8]  Aysen Demiroren,et al.  The application of ANN technique to automatic generation control for multi-area power system , 2002 .

[9]  Kyung-Bin Song,et al.  Extended integral control for load frequency control with the consideration of generation-rate constraints , 2002 .

[10]  J. Nanda,et al.  AUTOMATIC GENERATION CONTROL OF A HYDROTHERMAL SYSTEM WITH NEW AREA CONTROL ERROR CONSIDERING GENERATION RATE CONSTRAINT , 1990 .

[11]  Ali Feliachi On load frequency control in a deregulated environment , 1996, Proceeding of the 1996 IEEE International Conference on Control Applications IEEE International Conference on Control Applications held together with IEEE International Symposium on Intelligent Contro.

[12]  Zakariya Al-Hamouz,et al.  A new load frequency variable structure controller using genetic algorithms , 2000 .

[13]  Bernard Widrow,et al.  Application of neural networks to load-frequency control in power systems , 1994, Neural Networks.

[14]  P. Kundur,et al.  Power system stability and control , 1994 .

[15]  Mohammad Bagher Menhaj,et al.  Decentralized robust adaptive-output feedback controller for power system load frequency control , 2002 .

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

[17]  Hadi Saadat,et al.  Power System Analysis , 1998 .

[18]  N. Bengiamin,et al.  Variable Structure Control of Electric Power Generation , 1982, IEEE Transactions on Power Apparatus and Systems.