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Recent Trends in Electronics Communication Systems

Prediction of Excitation Current of Synchronous Machines Based on Neural Network Model

  1. Sumanta Dey
  2. Mita Halder
  3. Amit Dey

Abstract

There are several difficulties found to estimate the excitation current & and optimum input parameters of synchronous motors. Heuristic methods are frequently used to weightt the problem's parameters or optimum coefficients. As a result, a neural network model is modified in this study to explore the best parameters and estimate the excitation current of a synchronous motor with minimal prediction errors for both the testing dataset and cross validation. Excitation current variations are affected by four input factors, including load current, power factor, error, and changes in excitation current, when training this model. The experimental results reflects that the proposed neural network predicts the new data set effectively as well as enabled enables to predict best weighted value for optimum excitation current of synchronous motors.

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