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Penggunaan Fast Fourier Transform Pada Identifikasi Arc Fault Pada Berbagai Jenis Kabel Trysnawan, Mochammad Zulfikar; H.S, Hendik Eko; Anggriawan, Dimas Okky
INOVTEK - Seri Elektro Vol 2, No 3 (2020): INOVTEK Seri Elektro
Publisher : Politeknik Negeri Bengkalis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35314/ise.v2i3.1473

Abstract

Arc merupakan loncatan bunga api yang disebabkan karena adanya pelepasan energi dari kabel penghantar. Arc fault menghasilkan panas yang dapat merusak isolasi kawat sehingga dapat menyebabkan terjadinya bahaya kebakaran. Namun keterbatasan akan hal memonitoring seluruh jalur pengawatan menjadi kendala dalam pendeteksian secara dini adanya gangguan arcing. Dirancang sebuah alat identifikasi arc fault pada kabel berjenis serabut dan pejal, yang mana dapat mencegah kebakaran dikarenakan keterlambatan untuk mengamankan bahaya arcing. Pada alat ini memanfaatkan AMC1301 sebagai sensor tegangan dan sensor arus. Sistem ini bekerja mengamankan instalasi saat terjadi gangguan serta dapat mengirim kondisi secara real status dari jalur pengawatan (ada gangguan arc atau tidak). Kondisi dari sistem instalasi yang terbaca oleh sensor diolah oleh mikrokontroler dan metode yang digunakan adalah mendeteksi munculnya komponen frekuensi tinggi pada arus sistem menggunakan Fast Fourier Transform (FFT). Apabila mendeteksi adanya gangguan busur seri AC, maka mikrokontroler akan mengolah data dengan FFT dan diidentifikasi jenis kabel uji sesuai karakteristiknya ketika terjadi gangguan. Penelitian ini dibangun pada sistem tegangan rendah 220V/50Hz dengan arus gangguan sebesar 0,83A dengan beban resistif. Data pengujian menunjukkan bahwa AFCI dengan metode FFT mampu mendeteksi gangguan busur seri AC dan memberikan proteksi pada sistem dengan rata-rata waktu pemutusan 872 ms.
Identifikasi Jenis Gangguan Pada Jaringan Distribusi Menggunakan Metode Artificial Neural Network Aryaguna, Abel Aditya; Anggriawan, Dimas Okky; Suhariningsih, Suhariningsih
INOVTEK - Seri Elektro Vol 3, No 1 (2021): INOVTEK Seri Elektro
Publisher : Politeknik Negeri Bengkalis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35314/ise.v3i1.1954

Abstract

Berkembangnya kebutuhan masyarakat terhadap tenaga listrik saat ini meningkat pesat, sehingga perlindungan terhadap jaringan distribusi sangatlah penting untuk menjamin pelayanan tenaga listrik. Paper ini menyajikan algoritma yang diusulkan untuk identifikasi variasi tegangan durasi pendek. Artificial Neural Network (ANN) digunakan untuk mengidentifikasi 7 jenis varasi tegangan durasi pendek seperti sinyal normal, sag instantaneous, sag momentary, sag temporary, swell instantaneous, swell momentary, dan juga swell temporary. Simulasi untuk membangkitkan gangguan menggunakan software MATLAB Simulink yang telah disimulasikan dan mendapat nilai untuk input data ke ANN. Hasil algoritma yang diusulkan sangatlah efektif untuk identifikasi, dimana ANN dengan 5 x 5 neuron pada lapisan tersembunyi memiliki tingkat akurasi 100%.
Design of SEPIC Converter for Battery Charging System using ANFIS Suryono; Sudiharto, Indhana; Anggriawan, Dimas Okky; Jufriyadi, Mohammad
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 9, No. 2, May 2024
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v9i2.1954

Abstract

Rechargeable batteries are the most widely used medium for storing energy today. One type of rechargeable battery that is widely used is lithium-ion batteries. The large use of lithium-ion batteries in society requires companies to conduct research so that the life time of these batteries can last a long time and charging can take place quickly. Charging system at this time is less efficient in charging lithium batteries where the time needed is still quite long where when lithium batteries are charged with a long time can cause the battery to heat up quickly and can reduce the life time of the battery. To overcome this, a system is needed that can control the battery charger process so that the output voltage and current are constant and battery charging is faster. It is hoped that the SEPIC converter system can help many people who forget to unplug the power supply during the charging process so as to maintain the life time of the battery. Setting the output voltage and current in the DC-DC converter can be done using an Adaptive Neuro Fuzzy Inference System which aims to keep the output of SEPIC stable according to the setting point. In this system, the DC-DC converter used is a SEPIC converter which can increase and decrease the output voltage for battery charging. The battery charging process uses the CC-CV method. In the test, the average error is 0.025% where when the SOC is 60% to 80% the average error is 0.04% and when the SOC is 80% to 95% the average error is 0.0005%.
Identifikasi Gangguan Degradation Fault pada Photovoltaic Array berbasis Artificial Neural Network SUHARININGSIH, SUHARININGSIH; SUNARNO, EPYK; SALSABILA, MUTIARA NADHIFAH; ANGGRIAWAN, DIMAS OKKY; PRASETYONO, EKA
ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika Vol 12, No 1: Published January 2024
Publisher : Institut Teknologi Nasional, Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26760/elkomika.v12i1.36

Abstract

ABSTRAKEnergi terbarukan sudah mulai mendominasi dunia sejak puluhan tahun lalu, terutama listrik tenaga surya. Pada setiap instalasi PV terdapat gangguan yang sering terjadi, salah satunya adalah degradation fault. degradation fault merupakan jenis gangguan berupa perubahan warna pada lapisan Ethylene Vinyl Acetate dari yang berwarna putih menjadi kuning hingga kecoklatan. Perubahan warna tersebut disebabkan oleh usia pemakaian dan suhu yang terlalu panas dan dapat menyebabkan penurunan arus yang sangat drastis. Kejadian ini mengakibatkan penurunan Isc mencapai 13%. Hal ini tidak baik jika terus dibiarkan pada instalasi solar panel. Oleh karena itu, pada jurnal ini akan membahas pengidentifikasian degradation fault pada array PV dengan Artificial Neural Network. ANN akan mengidentifikasi adanya penurunan arus pada PV array. Dari hasil yang didapatkan bahwa penurunan arus mencapai 12% dan dapat mengidentifkasi adanya degradation fault.Kata kunci: degradation fault, discoloration, Ethylene Vinyl Acetate , short circuit current, artificial neural network ABSTRACTRenewable energy has started to dominate the world since decades ago, especially solar electricity. In every PV installation there are disturbances that often occur, one of which is a degradation fault. Degradation fault is a type of disturbance in the form of discoloration of the Ethylene Vinyl Acetate layer from white to yellow to brownish. The discoloration is caused by age of use and temperatures that are too hot and can cause a very drastic decrease in current. This incident resulted in a decrease in Isc reaching 13%. This is not good if it continues to be left on solar panel installations. Therefore, this journal will discuss the identification of degradation faults in PV arrays with Artificial Neural Networks. ANN will identify a decrease in current in the PV array. From the results obtained that the decrease in current reaches 12% and can identify a degradation fault.Keywords: degradation fault, discoloration, Ethylene Vinyl Acetate , short circuit current, artificial neural network
Development of TCR-FC Reactive Power Compensation Device with Fuzzy Logic Control in Electric Power Networks Sunarno, Epyk; Prasetyono, Eka; Anggriawan, Dimas Okky; Nugroho, Mochamad Ari Bagus; Eviningsih, Rachma Prilian; Suhariningsih, Suhariningsih; Nugraha, Anggara Trisna; Anggara Trisna Nugraha
Indonesian Journal of Electronics, Electromedical Engineering, and Medical Informatics Vol. 6 No. 4 (2024): November
Publisher : Jurusan Teknik Elektromedik, Politeknik Kesehatan Kemenkes Surabaya, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35882/ijeeemi.v6i4.12

Abstract

Utilization of electrical loads in predominantly inductive single-phase low-voltage power grids, the quality of electrical power becomes poor due to reactive power consumption resulting in a lack of power factor resulting in power loss, voltage drop, and decreased service life of the power grids. equipment. The research on reactive power compensation using TCR-FC aims to make improvements in improving the power factor in single-phase low-voltage electrical networks so that they have flexible control, do not experience excess compensation, have fast dynamic responses, and are space-saving. And can monitor voltage, current, and phase difference parameters through sensor readings to process data mathematically. When using electrical loads, the reactive power value is larger and the power factor is low below 0.85, the system controls the ignition angle of the TRIAC so that the current flowing into the reactor can be controlled by the reactive absorption measure of the fixed capacitor. So, it can improve the power factor. Simulation results can increase the power factor that exceeds the average value of 0.9 by 0.9797 with an error of 0.0288%. Hardware test results can increase the average power factor to exceed 0.9 by 0.9758 with an error of 0.1373%. in conclusion, reactive power compensation devices that use thyristor-controlled reactors and fixed capacitors can be more efficient than capacitor banks.
Multifunctional Digital Protection Relay for Voltage and Current Disturbances in Power Networks Riza, Andrian; Suhariningsih; Okky Anggriawan, Dimas; Sunaryo, Epyk
Emitor: Jurnal Teknik Elektro Vol 24, No 3: November 2024
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/emitor.v24i3.5313

Abstract

The protection system is an essential part of the electrical power system, designed to minimize disturbances quickly, accurately, and precisely. Excessive electricity use can lead to frequent voltage and current fluctuations, resulting in short circuits, significant current spikes, and equipment damage. In addition to voltage and current variations, some electrical equipment is highly sensitive to frequency changes. Therefore, a device is needed to provide protection, prevent damage to electrical equipment, and ensure reliability. This research focuses on developing a protection relay using digital technology to continuously monitor and analyze voltage, current, and frequency parameters. When a fault or an out-of-range parameter is detected, the relay activates to protect the electrical system. For current protection, an experiment with a standard inverse setting at four different points was conducted, achieving an average reliability of 7.5%. For the very inverse setting with four different points, the average reliability was 5.79%. Voltage testing involved setting the overvoltage to the standard value of 231 volts and using various time delay types, resulting in an average reliability of 6%. This device is expected to protect electrical equipment that is highly sensitive to current, frequency, and voltage fluctuations.
Inrush Current Based on Fast Fourier Transform Zamzami, Mochamad Ilham; Prasetyono, Eka; Anggriawan, Dimas Okky; Yuliana, Mike
INTEK: Jurnal Penelitian Vol 8 No 2 (2021): October 2021
Publisher : Politeknik Negeri Ujung Pandang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31963/intek.v8i2.2940

Abstract

Advances in technology have caused the use of electricity to increase rapidly. With advances in technology, this is followed by the use of increasingly efficient electrical components or equipment. This more efficient electrical equipment causes the impedance of the component to be smaller, causing a surge in current when it is turned on. This current surge, if not followed by appropriate safety precautions, will be damage other components. Each load has different waveform characteristics and current transient peaks. For this reason, it is necessary to analyze the transient condition of a load to overcome this. This paper will explain the characteristics of the inrush current of the load due to ignition. There are three loads used in this study, namely resistive, capacitive and inductive loads. Then the use of this load is simulated by giving different ignition angle values, namely 0, 60, and 90 degrees. The analysis used is the Fast Fourier Transform (FFT) method which is a derivative of the Discrete Fourier Transform. The inrush current spectrum in this simulation is simulated using Simulink MATLAB with switching system modeling using TRIAC. This inrush current simulation data collection uses a sampling frequency of 100 Khz and will be analyzed in the first of 5 cycles. For each load in this paper, the harmonic values for each ignition angle will be presented. The simulation results show that the inrush current is caused by the ignition angle value used and because of components that can deviate energy such as inductors and capacitors as well as components which at the time of starting have a low impedance value such as incandescent lamps. The simulation also shows that the use of switching components for setting the ignition angle causes an increase in the value of Total Harmonic Distortion (THD) but the peak current in the first cycle when the ignition angle is set decreases.
Real-Time Detection of Power Quality Disturbance Using Fast Fourier Transform and Adaptive Neuro-Fuzzy Inference System Syahrin, Ahmad Alvi; Anggriawan, Dimas Okky; Prasetyono, Eka; Sunarno, Epyk; Wahjono, Endro; Sudiharto, Indhana; Suhariningsih, Suhariningsih
Jurnal Rekayasa Elektrika Vol 20, No 1 (2024)
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17529/jre.v20i1.33695

Abstract

Power quality disturbances cause equipment damage or financial losses. Therefore, the electric power system needs to identify and distinguish any power quality disturbances to reduce problems. This paper proposes hybrid methods combining FFT and ANFIS algorithm for detection of power quality disturbances. There are 11 types of power quality disturbances that can be detected, such as sag, swell, undervoltage, overvoltage, voltage flicker, voltage harmonic, sag + harmonic, swell + harmonic, undervoltage + harmonic, overvoltage + harmonic, and flicker + harmonic. The parameters used to detect disturbances are Vrms, Duration, THDv (Total Harmonic Distortion voltage), and Fluctuation-Count. The detection process starts by sensing voltage and calculating all the parameters, where THDv was obtained by Fast Fourier Transform. All the parameters such as Vrms, Duration, THDv, and Fluctuation-Count are processed by Adaptive Neuro-Fuzzy Inference System, and the result is the type of disturbance. Matlab simulations show that the suggested method performs outstandingly to identify 11 type of Power Quality Disturbances with 99.3% accuracy.
Rancang Bangun 3 Phase Energy Meter Untuk Analisis Kualitas Daya Di Industri Wahyudi, Sri; Prasetyono, Eka; Anggriawan, Dimas Okky; Yuliana, Mike; Budikarso, Anang
JURNAL INTEGRASI Vol. 15 No. 1 (2023): Jurnal Integrasi - April 2023
Publisher : Pusat Penelitian dan Pengabdian Masyarakat Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/ji.v15i1.3244

Abstract

The quality of electric power is one of the most important things in the industrial world, with good power quality, industrial efficiency will also increase which will result in savings in production costs. Energy consumption must also be monitored in such a way for the purposes of analyzing electrical energy efficiency. Therefore, the author designed a tool called a 3 phase energy meter that can monitor energy consumption and power quality for industry with a 3 phase electrical system. The 3 phase energy meter is equipped with an IoT system so that the observation of the measurement results of every electrical machine system in the industry can be done at one point without having to go to the location. The hope is that with the 3 phase energy meter, it can improve production efficiency through power quality analysis.