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Adaptive Power System Stabilizer Using ANFIS and Genetic Algorithms

  • Jesús Fraile-Ardanuy
  • Pedro J. Zufiria
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3512)

Abstract

This paper presents an adaptive Power System Stabilizer (PSS) using an Adaptive Network Based Fuzzy Inference System (ANFIS) and Genetic Algorithms (GAs). Firstly, genetic algorithms are used to tune a conventional PSS on a wide range of operating conditions and then, the relationship between these operating points and the PSS parameters is learned by the ANFIS. The ANFIS optimally selectes the classical PSS parameters based on machine loading conditions. The proposed stabilizer has been tested by performing nonlinear simulations using a synchronous machine-infinite bus model. The results show the robustness and the capability of the stabilizer to enhance system damping over a wide range of operating conditions and system parameter variations.

Keywords

Genetic Algorithm Power System Fuzzy Inference System Adaptive Network Base Fuzzy Inference System Synchronous Generator 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Jesús Fraile-Ardanuy
    • 1
  • Pedro J. Zufiria
    • 1
  1. 1.Grupo de Redes Neuronales, ETSI TelecomunicaciónUPMSpain

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