• DocumentCode
    3774860
  • Title

    Neural modeling of the electrical power system development based on IEEE RTS test data

  • Author

    Jerzy Tch?rzewski;Maciej Pytel

  • Author_Institution
    Institute of Computer Science, University of Natural Sciences and Humanities, Siedlce, Poland
  • fYear
    2015
  • fDate
    7/1/2015 12:00:00 AM
  • Firstpage
    1
  • Lastpage
    7
  • Abstract
    The paper contains selected results of research related to neural modeling of electrical power system development (EPS or EP System). Numerical data presented in paper [1, 8] were used to teach the artificial neural network (ANN) a model of EP system development. The ANN was designed in the MATLAB and Simulink environment using the Neural Network Toolbox. The generated model was used to perform simulation to examine sensitivity in Simulink. On the basis of the simulation model a comparative study was performed to compare responses of the model and the IEEE RTS test system. Sensitivity of the model was also examined by measuring the response of the model to the following input functions: sinusoid, unit step, Dirac impulse (Dirac delta function), etc. The results obtained were interpreted on the basis of the control and systems theory.
  • Keywords
    "Artificial neural networks","Training","Load modeling","Data models","Reactive power","Mathematical model","Software packages"
  • Publisher
    ieee
  • Conference_Titel
    Modern Electric Power Systems (MEPS), 2015
  • Type

    conf

  • DOI
    10.1109/MEPS.2015.7477168
  • Filename
    7477168