Load Identification Using Harmonic Based on Probabilistic Neural Network

  • Dimas Okky Anggriawan Politeknik Elektronika Negeri Surabaya
  • Aidin Amsyar Politeknik Elektronika Negeri Surabaya
  • Eka Prasetyono Politeknik Elektronika Negeri Surabaya
  • Endro Wahjono Politeknik Elektronika Negeri Surabaya
  • Indhana Sudiharto Politeknik Elektronika Negeri Surabaya
  • Anang Tjahjono Politeknik Elektronika Negeri Surabaya
Keywords: Harmonic, FFT, Probabilistic Neural Network, Loads


Due to increase power quality which are caused by harmonic distortion it could be affected malfunction electrical equipment. Therefore, identification of harmonic loads become important attention  in the power system. According to those problems, this paper proposes a Load Identification using harmonic based on probabilistic neural network (PNN). Harmonic is obtained by experiment using prototype, which it consists of microcontroller and current sensor. Fast Fourier Transform (FFT) method to analyze of current waveform on loads become harmonic load data. PNN is used to identify the type of load. To load identification, PNN is trained to get the new weight. Testing is conducted To evaluate of the accuracy of the PNN from combination of four loads. The results demonstrate that this method has high accuracy to determine type of loads based on harmonic load


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How to Cite
Anggriawan, D. O., Amsyar, A., Prasetyono, E., Wahjono, E., Sudiharto, I., & Tjahjono, A. (2019). Load Identification Using Harmonic Based on Probabilistic Neural Network. EMITTER International Journal of Engineering Technology, 7(1), 71-82. https://doi.org/10.24003/emitter.v7i1.330