EMITTER International Journal of Engineering Technology
Vol 7 No 1 (2019)

Load Identification Using Harmonic Based on Probabilistic Neural Network

Anggriawan, Dimas Okky (Unknown)
Amsyar, Aidin (Unknown)
Prasetyono, Eka (Unknown)
Wahjono, Endro (Unknown)
Sudiharto, Indhana (Unknown)
Tjahjono, Anang (Unknown)

Article Info

Publish Date
15 Jun 2019


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

Copyrights © 2019

Journal Info





Computer Science & IT


EMITTER International Journal of Engineering Technology is a BI-ANNUAL journal published by Politeknik Elektronika Negeri Surabaya (PENS). It aims to encourage initiatives, to share new ideas, and to publish high-quality articles in the field of engineering technology and available to everybody at ...