Performance analysis of adaptive neural network frequency controller for thermal power systems

  • Authors:
  • Ognjen Kuljaca;Sejid Tesnjak;Vladimir Koroman

  • Affiliations:
  • Systems Research Institute, Department of Advanced Technologies, Alcorn State University, Alcorn State, MS;Department of Power Systems, Faculty of Electrical Engineering and Computing, University of Zagreb, Zagreb, Croatia;Control Engineering Department, Brodarski Institute, Zagreb, Croatia

  • Venue:
  • ACMOS'07 Proceedings of the 9th WSEAS international conference on Automatic control, modelling and simulation
  • Year:
  • 2007
  • Adaptive control based on neural network system identification

    EHAC'12/ISPRA/NANOTECHNOLOGY'12 Proceedings of the 11th WSEAS international conference on Electronics, Hardware, Wireless and Optical Communications, and proceedings of the 11th WSEAS international conference on Signal Processing, Robotics and Automation, and proceedings of the 4th WSEAS international conference on Nanotechnology

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Abstract

An adaptive neural network control scheme for thermal power system is described. No off-line training is required for the proposed neural network controller. The online tuning algorithm and neural network architecture are described. The performance of the controller is illustrated via simulation for different changes in process parameters. Performance of neural network controller is compared with conventional proportional-integral control scheme for frequency control in thermal power systems.