Load Identification Using Harmonic Based on Probabilistic Neural Network
| Main Authors: | Anggriawan, Dimas Okky, Amsyar, Aidin, Prasetyono, Eka, Wahjono, Endro, Sudiharto, Indhana, Tjahjono, Anang |
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| Format: | Article info application/pdf eJournal |
| Bahasa: | eng |
| Terbitan: |
Politeknik Elektronika Negeri Surabaya (PENS)
, 2019
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| Subjects: | |
| Online Access: |
http://emitter.pens.ac.id/index.php/emitter/article/view/330 http://emitter.pens.ac.id/index.php/emitter/article/view/330/132 |
Daftar Isi:
- 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