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All Journal TELKOMNIKA (Telecommunication Computing Electronics and Control) ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika EMITTER International Journal of Engineering Technology JTT (Jurnal Teknologi Terpadu) JURNAL INTEGRASI Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Energi & Kelistrikan INTEK: Jurnal Penelitian Jurnal Rekayasa elektrika Emitor: Jurnal Teknik Elektro Indonesian Journal of Electronics, Electromedical Engineering, and Medical Informatics
Dimas Okky Anggriawan
Politeknik Elektronika Negeri Surabaya
Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Energy Engineering Health Professions Materials Science & Nanotechnology Mechanical Engineering Other

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Implementation of Fast Fourier Transform and Artificial Neural Network in Series Arc Fault Identification and Protection System on DC Bus Microgrid Dimas Okky Anggriawan; Epyk Sunarno; Eka Prasetyono; Suhariningsih Suhariningsih; Muhammad Fauzi
Jurnal Teknologi Terpadu Vol 11, No 2 (2023): JTT (Jurnal Teknologi Terpadu)
Publisher : Pusat Penelitian dan Pengabdian Kepada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32487/jtt.v11i2.1869

Abstract

A microgrid is a cluster of electrical sources and loads that are interconnected and synchronized. Microgrid operation is typically divided into two modes, isolated or connected to the grid with a single or standalone control system. In this context, it can enhance the reliability and quality of electricity supply for connected customers. When using a microgrid system, it is important to consider the risk of series arc faults. Series arc faults are sudden bursts of flames resulting from ionization of gas between two electrode gaps. These faults can occur due to manufacturing defects, installation Errors, aging, or corrosion on conductor rods, leading to imperfect connections. Detecting series arc faults in DC microgrid system operations can be challenging using standard protective devices. Failure in the protection system can pose risks of fire, electrical shock hazards, and power loss in the DC microgrid.Therefore, a device has been designed to detect series arc faults by utilizing the fast Fourier transform method and artificial neural network, which function to analyze DC signal and make decisions when faults occur by examining the average sum of current frequency values during normal and fault conditions. In this study, the average sum of current frequency values during normal conditions was found to range from 0.35437 to 0.36906 A, while during fault conditions, it ranged from 0.21450 to 0.22793 A, with an average protection identification time of 1087 ms and an ANN output accuracy of 99.98%.
Implementasi Fuzzy Logic Untuk Identifikasi Jenis Gangguan Tegangan Secara Realtime Ahmad Alvi Syahrin; Dimas Okky Anggriawan; Eka Prasetyono
Jurnal Rekayasa Elektrika Vol 16, No 3 (2020)
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17529/jre.v16i3.17692

Abstract

In the modern era, AC voltage variations are still often a problem. This variation causes power quality decrease even damage the equipment. Voltage variations that often occur are short and long duration. The variation consist of 6 types namely Interruption, Sag, Swell, Sustained-Interruption, Undervoltage, Overvoltage. To facilitate repairs when there is a voltage variation in the electric power system, it is necessary to have an identification that can detect and distinguish any interference that occurs. Therefore, this paper proposes a fuzzy logic method for identifying types of voltage variations. This type of voltage variation identifier requires a disturbance simulator as a voltage source with varying values. To distinguish between short duration and long duration disturbances, is the time duration of the disturbance appears. The design of the voltage variation identification algorithm uses the sugeno fuzzy inference system with 2 inputs namely magnitude vrms and timer, and 1 output is the type of voltage interference. Moreover, prototype design using AMC1200 voltage sensor, microcontroller, and display. To validate the proposed algorithm, compared with standard measuring tools and simulations. Results show that the proposed algorithm has a very good performance with an accuration compared to the standard measuring instrument of 99.8%.
Parallel Balancing Battery using Adaptive Power Sharing and ANN SOC Estimator Mokhamad Zuhal Muflih; Gilang Andaru Trinandana; Eka Prasetyono; Dimas Okky Anggriawan
Jurnal Rekayasa Elektrika Vol 17, No 3 (2021)
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17529/jre.v17i3.20671

Abstract

The battery balancing method is commonly used in cell circuits and battery circuits to maintain the power continuity on the DC Bus. The power continuity on the DC Bus is guaranteed if the load continues to get a power source, even if either the battery or power supply malfunctions. Besides, the battery balancing method is also used to protect the battery from excessive charging current pliers flowing into the battery. Therefore, the State-of-Charge (SoC) should be concern in balancing the maintained battery condition on both systems and avoiding overcharging. Artificial Neural Network (ANN) is used in this paper to determine the value of battery SoC. Based on simulations using MATLAB 2018, SoC values with ANN showed accurate results with error values below 0.1%. Based on the simulation results, the two batteries, which are arranged to have a difference of SoC value of 0.3%, will achieve a balanced SoC value for 28.45 seconds from the simulation.
Identification of Power Quality Disturbances Based on Fast Fourier Transform and Artificial Neural Network Dimas Okky Anggriawan; Endro Wahjono; Indhana Sudiharto; Anang Budikarso
Jurnal Rekayasa Elektrika Vol 19, No 1 (2023)
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17529/jre.v19i1.27120

Abstract

This paper presents the proposed algorithms for the identification of Short Duration RMS Variations and Long Duration RMS Variations combined with harmonic. The proposed algorithms are Fast Fourier Transform (FFT) and Artificial Neural Network (ANN). The Algorithms identify nine types of Power Quality (PQ) disturbances such as normal signal, voltage sag, voltage swell, under voltage, over voltage, voltage sag combined harmonic, voltage swell combined harmonic, undervoltage combined harmonic, and over voltage combined harmonic. FFT is used to obtain the frequency spectrum of each PQ disturbance with frequency sampling of 1000 Hz, data length of 200. Output FFT is used to input data for ANN. Output ANN is a type of nine PQ disturbances. The result shows that proposed algorithms (FFT combined ANN) are effective for identification, which ANN with 20 neurons in the hidden layer has an accuracy of approximately 99.95 %
Pendeteksian Harmonisa Arus Berbasis Feed Forward Neural Network Secara Real Time Endro Wahjono; Dimas Okky Anggriawan; Achmad Luki Satriawan; Aji Akbar Firdaus; Eka Prasetyono; Indhana Sudiharto; Anang Tjahjono; Anang Budikarso
Jurnal Rekayasa Elektrika Vol 16, No 1 (2020)
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17529/jre.v16i1.15093

Abstract

The development of power electronics converters has been widespread in the industrial, commercial, and home applications. The device is considered to produce harmonics in non-linear loads. Harmonics cause a decrease in power quality in the electric power system. To prevent a decrease in power quality caused by harmonics in the power system, the detection of harmonics has an important role. Therefore, this paper proposed feed forward neural network (FFNN) for harmonic detection. The design of harmonic detection device is designed with a feed forward neural network method that it has two stages of information processing, namely the training stage and the testing stage. FFNN has input harmonics and THDi as output. To detect harmonics, frst training is conducted to recognize waveform patterns and calculate the fast fourier transform (FFT) process offline. Prototype using the AMC1100DUB current sensor, microcontroller and display. To validate the proposed algorithm, compared by standard measurement tool and FFT. The results show the proposed algorithm has good performance with the average percentage error compared by standard measurement tool and FFT of 5.33 %.
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.
Co-Authors Abel Aditya Aryaguna Achmad Luki Satriawan Ahmad Alvi Syahrin Alia, Diana Amsyar, Aidin Amsyar, Aidin Anang Budikarso Anang Budikarso, Anang Anang Tjahjono, Anang Anggara Trisna Nugraha Aryaguna, Abel Aditya Bambang Sumantri Dirhamsyah Dirhamsyah Eka Prasetyono, Eka Endro Wahjono Endro Wahjono, Endro Epyk Sunarno Era Purwanto Eva Inaiyah Agustin Firdaus, Aji Akbar Fuad, Muchamad Chaninul Fuad, Muchamad Chaninul Gilang Andaru Trinandana H.S, Hendik Eko Hendik Eko H.S Indhana Sudiharto Jufriyadi, Mohammad Khafidli, Muhammad Khanif Khalin Khalin Mentari Putri Jati Mike Yuliana MOCHAMAD ARI BAGUS NUGROHO Mochammad Zulfikar Trysnawan Mokhamad Zuhal Muflih Muhammad Fauzi Novie Ayub Windarko Rachma Prilian Eviningsih, Rachma Prilian Rheinanda, Audya Elisa Riza, Andrian SALSABILA, MUTIARA NADHIFAH Suhariningsih Suhariningsih Suhariningsih Suhariningsih Sunaryo, Epyk Suryono sutedjo Sutedjo Sutedjo Sutedjo Syahrin, Ahmad Alvi Tesa Eranti Putri Trysnawan, Mochammad Zulfikar Wahyudi, Sri Yunardi, Riky Tri Zamzami, Mochamad Ilham