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Nonlinear identification of the external power system dynamic equivalent for the study system
Proc of 27th Chinese Control Conference IEEE-CCC08 (2008)
  • Hamidreza Radmanesh, Shahed University
  • Hamed Shakouri G., University of Tehran
  • Mehdi Karrari
Abstract

Based on the concept of the external power system dynamic equivalent for the study system, in this paper a reduced-order artificial neural network is proposed, which is constructed to model the external part. The mastermind behind the proposed method is to identify the external part as a dynamic-algebraic ANN, and this separation between dynamic equations in the state space form and algebraic equations is useful to solve the prediction problem. To obtain this model, the system should be excited by some disturbances, and according to the measured data on the boundary nodes, identification procedure is accomplished. Therefore, the trained network can be used to predict behavior of the external system in a high degree of accuracy.

Keywords
  • Dynamic equivalent,
  • Multi-machine system,
  • Artificial neural networks,
  • Nonlinear identification
Publication Date
July, 2008
Citation Information
Hamidreza Radmanesh, Hamed Shakouri G. and Mehdi Karrari. "Nonlinear identification of the external power system dynamic equivalent for the study system" Proc of 27th Chinese Control Conference IEEE-CCC08 Vol. 3 (2008)
Available at: http://works.bepress.com/hamidreza_radmanesh/8/