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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

Author-ID : 2455449

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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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

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

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.

Load Identification Using Harmonic Based on Probabilistic Neural Network Anggriawan, Dimas Okky; Amsyar, Aidin; Prasetyono, Eka; Wahjono, Endro; Sudiharto, Indhana; Tjahjono, Anang
EMITTER International Journal of Engineering Technology Vol 7 No 1 (2019)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

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 attentionÂ 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

A Full-Bridge Bidirectional DC-DC Converter with Fuzzy Logic Voltage Control for Battery Energy Storage System Prasetyono, Eka; Sunarno, Epyk; Fuad, Muchamad Chaninul; Anggriawan, Dimas Okky; Windarko, Novie Ayub
EMITTER International Journal of Engineering Technology Vol 7 No 1 (2019)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

Renewable energy sources require an energy storage system because its are fluctuating and electricity producing at certain times, even sometimes not in accordance with the needs of the load. To maintain continuity of electricity, smart battery energy storage system is needed. Therefore, this paper of a full-bridge bidirectional DC-DC Converter (FB-BDC) with Fuzzy Logic Control (FLC) is designed and implemented for battery energy storage application. The FLC has error and delta error of voltage level as input and duty cycle of FB-BDC as output. The FB-BDC is controlled by a microcontroller ARM Cortex-M4F STM32F407VG for voltage mode control. The FB-BDC topology is selected becuase battery storage system needed isolated and need high voltage ratio both for step-up and step-down. The main purpose of FB-BDC to perform bidirectional energy transfer both of DC-Bus and battery. Moreover, FB-BDC controls the DC-Bus voltage according to referenced value. The power flow and voltage on DC-Bus is controlled by FLC with voltage mode control. The experiment result shows the ability of FLCÂ voltage mode control to control FB-BDC on regulate charging voltage with an error 1% and sharing voltage 1.5% form referenced value.

Series Arc Fault Breaker in Low Voltage Using Microcontroller Based on Fast Fourier Transform Anggriawan, Dimas Okky; Rheinanda, Audya Elisa; Khafidli, Muhammad Khanif; Prasetyono, Eka; Windarko, Novie Ayub
EMITTER International Journal of Engineering Technology Vol 9 No 2 (2021)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24003/emitter.v9i2.615

Series Arc Fault is one of the disturbances of arcing jump is caused by gas ionization between two ends of damaged conductors or broken wire forming a gap in the insulator. Series arc fault is the primary driver of electrical fire. However, lack of knowledge of the disturbance of series arc fault causes the problem of electrical fire not be mitigated. Magnitude current is not capable to detect of series arc fault. Therefore, this paper proposes fast fourier transform (FFT) to detect series AC arc fault in low voltage using microcontroller ARM STM32F7NGH in real time. A cheap and high speed of microcontroller ARM STM32F7NGH can be used for FFT computation to transform signal in time domain to frequency domain. Moreover, in this paper, protection of series AC arc fault is proposed in the real time mode. In this experimental process, some various experiments are tested to evaluate the reliability of FFT and protection with various load starts from 1 A, 2 A, 3 A, 4 A in resistive load. The result of this experiment shows that series AC arc fault protection with STM32F7 microcontroller and FFT algorithm can be utilized to ensure series AC arc fault properly.

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

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