Design of decentralized neuron based LFC in a deregulated power system

  • Authors:

  • Heidar Ali Shayanfar;Hossein Shayeghi

  • Affiliations:

  • Electrical Engineering Department, Iran University of Science and Technology, Tehran, Iran;Technical Engineering Department, University of Mohaghegh Ardebili, Ardebil, Iran

  • Venue:
  • ICAI'05/MCBC'05/AMTA'05/MCBE'05 Proceedings of the 6th WSEAS international conference on Automation & information, and 6th WSEAS international conference on mathematics and computers in biology and chemistry, and 6th WSEAS international conference on acoustics and music: theory and applications, and 6th WSEAS international conference on Mathematics and computers in business and economics
  • Year:
  • 2005

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Abstract

This paper presents a new decentralized Artificial Neural Network (ANN) controller based on the mixed H2/H∞ control technique for Load Frequency Control (LFC) in a deregulated power system. To achieve decentralization, the effects of possible contracted scenarios and interfaces between control areas are treated as a set of new input disturbance signals. In order to account modeling uncertainties, cover practical constraints on control action and minimize the effects of area load disturbances, the idea of mixed H2/H∞ control technique is being used for training ANN based controller. This newly developed design strategy combines advantage of the ANN and mixed H2/H∞ control techniques for improveing robust performance and leads to a flexible controller with simple structure, which can be useful in real world complex power systems. The proposed method is tested on a two-area power system to demonstrate its robust performance with possible contracted scenarios under large load demands and modeling uncertainties. The results of proposed controller are compared with mixed H2/H∞ and PI controllers in the presence of Generation Rate Constraints (GRC).