Sartika, Nike
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Flutter Framework Implementation for Over Current Relay and Ground Fault Relay Setting Applications in 20 kV Distribution Systems Sartika, Nike; Maulidan, Muhammad Akmal; Mulyana, Edi
Jurnal Pendidikan Multimedia (Edsence) Volume 6 No 2 (December 2024)
Publisher : Universitas Pendidikan Indonesia (UPI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17509/edsence.v6i2.76176

Abstract

In the distribution system, there are several faults such as blackouts due to errors in the coordination of the protection relay. To minimize excessive damage to the electrical system, components such as over current relays (OCR) are needed to overcome inter-phase faults and ground fault relays (GFR) to overcome phase-to-ground faults. The setting process that has been carried out so far is still ineffective, so a system is needed to simplify the setting process. Flutter is a development framework from Google that can release applications in the form of Android or iOS. This study aims to simplify the OCR and GFR setting process using a mobile application. Application development uses the waterfall method. The test results consisting of blackbox alpha, beta and manual calculations show that this application is running according to the expected functionality. In addition, the results of the settings that have been done are the OCR setting current of 400 A in zone 1 and 300 A in zone 2 with a Time Multiplier Setting (TMS) value of 0.2 in zone 1 and 0.05 in zone 2. While the GFR setting current is 80 A in zone 1 and 60 A in zone 2 with a TMS value of 0.175 in zone 1 and 0.05 in zone 2. From these setting values, the OCR time difference (Δt) value is then obtained around 0.6 seconds and 0.8 seconds for GFR. This shows that the OCR and GFR are in good condition.
DIAGNOSIS KEGAGALAN TRANSFORMATOR DAYA MENGGUNAKAN ALGORITMA K-NEAREST NEIGHBORS DAN ARTIFICIAL NEURAL NETWORK BERBASIS DISSOLVED GAS ANALYSIS Hidayat, Rafi Maulana; Media, Galih; Sartika, Nike; Kamelia, Lia
Transmisi: Jurnal Ilmiah Teknik Elektro Vol 27, No 3 Juli (2025): TRANSMISI: Jurnal Ilmiah Teknik Elektro
Publisher : Departemen Teknik Elektro, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/transmisi.27.3.140-148

Abstract

Dissolved Gas Analysis (DGA) merupakan metode untuk mengidentifikasi jenis kegagalan pada transformator dengan menilai jumlah gas yang terkandung pada minyak isolasi transformator. DGA memiliki beberapa metode dalam menganalisis dan mengidentifikasi jenis kegagalan berdasarkan jenis gas yang terlarut. Tetapi, dalam jumlah data yang besar metode ini menjadi sulit dan memerlukan keahlian dalam mendeteksi kegagalan secara grafis. Penelitian ini bertujuan untuk meningkatkan akurasi diagnostik kegagalan transformator dengan mengimplementasikan serta membandingkan algoritma K-Nearest Neighbors (KNN) dengan algoritma Artificial Neural Network (ANN) pada setiap metode konvensional DGA yaitu Roger Ratio, Duval Triangle, Four Gases dan Duval pentagon dalam mengklasifikasikan jenis kegagalan. Sebanyak 822 sampel dataset digunakan untuk melatih dan memvalidasi model yang digunakan. Berdasarkan hasil penelitian diagnosis kegagalan transformator menunjukan bahwa metode grafis memberikan hasil yang paling efektif dalam mendiagnosis jenis kegagalan transformator dibandingkan dengan metode rasio. Selain itu penggunaan algoritma KNN memberikan hasil yang lebih baik dibandingkan dengan algoritma ANN dalam meningkatkan akurasi diagnostik dengan memperoleh akurasi tertinggi sebesar 98% pada duval triangle.