Deteksi dan Klasifikasi Gangguan Kualitas Daya Berbasis S-Transform dan Artificial Neural Network

Firdaus, Rama Kurniawan (2019) Deteksi dan Klasifikasi Gangguan Kualitas Daya Berbasis S-Transform dan Artificial Neural Network. Undergraduate thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Kualitas daya listrik menjadi hal yang perlu diperhatikan seiring dengan perkembangan teknologi dimana peralatan listrik modern yang memiliki kepekaan tinggi terhadap gangguan kualitas daya listrik. Gangguan kualitas daya listrik dapat berdampak pada ketidaksempurnaan operasi peralatan listrik, menyebabkan kerusakan peralatan listrik yang berujung pada kerugian ekonomi. Penurunan kualitas daya listrik disebabkan oleh gangguan yang berupa voltage sag, voltage swell, gangguan sesaat, harmonisa, flicker yang akan menyebabkan kegagalan operasi, ketidakstabilan sistem, memperpendek umur peralatan, dan lain sebagainya. Pada penelitian ini menggunakan S-transform untuk mengekstraksi informasi atau fitur dari sinyal gangguan kualitas daya. Beberapa jenis gangguan kualitas daya memilki sinyal dengan karakteristik non-stasioner. S-Transform memiliki kemampuan untuk mengekstrak fitur yang terkandung dalam sinyal arus dan tegangan yang terdampak gangguan kualitas daya dengan karakteristik non-stasioner dengan proses komputasi yang ringkas serta penggunaan memori yang rendah bila dibandingkan dengan metode lain. Hasil ekstraksi fitur dengan S-Transform selanjutnya akan digunakan untuk input Artificial Neural Netwok (ANN). Dalam penelitian ini ANN memegang peranan dalam pengklasifikasian gangguan kualitas daya. =============================================================================================== Power quality has become an important issue for electric utilities and its customers. In this modern era, many electric devices is very sensitive to power quality disturbance when in operation. The disturbance may affect the operation of electric utilities and its customers that lead to breakdown and economical issue. Power quality degradation caused by sag, swell, harmonics, flicker, notching and spike will reduce lifetime of the electric devices. In this research using S-transform to extract the features that contained in the power quality disturbance signal. A few of power quality disturbance event have non-stationary signal characteristic. Stransform has ability to extracting the features from the signal that affected by the disturbance with the low computational and low memory usage compared with other signal extracting method. The extracting result from the S-transform will be used as input of the Artificial Neural Network (ANN). The ANN has a role in this research to recognize the power quality disturbance event from the signal

Item Type: Thesis (Undergraduate)
Additional Information: RSE 621.31 Fir d-1 2019
Uncontrolled Keywords: Gangguan kualitas daya, S-transform, Artificial Neural Network (ANN)
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK1007 Electric power systems control
Divisions: Faculty of Industrial Technology > Electrical Engineering > 20201-(S1) Undergraduate Thesis
Depositing User: Rama Kurniawan Firdaus
Date Deposited: 11 Jun 2021 08:27
Last Modified: 11 Jun 2021 08:27
URI: https://repository.its.ac.id/id/eprint/60507

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