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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)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (903.883 KB) | DOI: 10.24003/emitter.v7i1.333

Abstract

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 FLC  voltage mode control to control FB-BDC on regulate charging voltage with an error 1% and sharing voltage 1.5% form referenced value.
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)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (529.473 KB) | DOI: 10.24003/emitter.v7i1.330

Abstract

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 attention  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
Hardware implementation of series DC arc fault protection using fast Fourier transform Dirhamsyah Dirhamsyah; Diana Alia; Dimas Okky Anggriawan
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 19, No 5: October 2021
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v19i5.20521

Abstract

This paper proposes method of series DC arc fault protection using low cost microcontroller. Series DC arc fault occurs when gap between conductor or wire flows a current. Series DC arc fault can cause fire hazard if do not detected and protected. However, Series DC arc fault is difficult to detected using conventional protection. To detect series DC arc fault accurately using fast Fourier transform (FFT). FFT is used to transform signal in time domain to frequency domain. Series DC arc fault has different characteristic compared by normal current in frequency domain. Therefore, the proposed algorithm for protection of series DC arc fault based on magnitudes of the current in frequency domain. Hardware system is implemented by 100 V DC power supply and DC arc fault generator. Test result is conducted experimentally under varying of load current such as 2 A, 2.5 A, 3 A, 3.5 A, 4 A and 5 A. Experimental testing results show that Series DC arc fault protection has time for trip of 0.48 s, 0.26 s, 1.04 s, 0.68 s, 0.44 s and 0.48, respectively. The fastest time for trip is 0.26 s with current of 2.5 A. Therefore, the proposed algorithm for series DC arc fault protection can operate to trip accurately and have the good performance.
Short-term photovoltaics power forecasting using Jordan recurrent neural network in Surabaya Aji Akbar Firdaus; Riky Tri Yunardi; Eva Inaiyah Agustin; Tesa Eranti Putri; Dimas Okky Anggriawan
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 18, No 2: April 2020
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v18i2.14816

Abstract

Photovoltaic (PV) is a renewable electric energy generator that utilizes solar energy. PV is very suitable to be developed in Surabaya, Indonesia. Because Indonesia is located around the equator which has 2 seasons, namely the rainy season and the dry season. The dry season in Indonesia occurs in April to September. The power generated by PV is highly dependent on temperature and solar radiation. Therefore, accurate forecasting of short-term PV power is important for system reliability and large-scale PV development to overcome the power generated by intermittent PV. This paper proposes the Jordan recurrent neural network (JRNN) to predict short-term PV power based on temperature and solar radiation. JRNN is the development of artificial neural networks (ANN) that have feedback at each output of each layer. The samples of temperature and solar radiation were obtained from April until September in Surabaya. From the results of the training simulation, the mean square error (MSE) and mean absolute percentage error (MAPE) values were obtained at 1.3311 and 34.8820, respectively. The results of testing simulation, MSE and MAPE values were obtained at 0.9858 and 1.3311, with a time of 4.591204. The forecasting has minimized significant errors and short processing times.
Load Identification Using Harmonic Based on Probabilistic Neural Network Dimas Okky Anggriawan; Aidin Amsyar; Eka Prasetyono; Endro Wahjono; Indhana Sudiharto; Anang Tjahjono
EMITTER International Journal of Engineering Technology Vol 7 No 1 (2019)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (529.473 KB) | DOI: 10.24003/emitter.v7i1.330

Abstract

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 attention  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 Eka Prasetyono; Epyk Sunarno; Muchamad Chaninul Fuad; Dimas Okky Anggriawan; Novie Ayub Windarko
EMITTER International Journal of Engineering Technology Vol 7 No 1 (2019)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (903.883 KB) | DOI: 10.24003/emitter.v7i1.333

Abstract

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 FLC  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 Dimas Okky Anggriawan; Audya Elisa Rheinanda; Muhammad Khanif Khafidli; Eka Prasetyono; Novie Ayub Windarko
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

Abstract

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.
Identifikasi Jenis Gangguan Pada Jaringan Distribusi Menggunakan Metode Artificial Neural Network Abel Aditya Aryaguna; Dimas Okky Anggriawan; 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%.
Penggunaan Fast Fourier Transform Pada Identifikasi Arc Fault Pada Berbagai Jenis Kabel Mochammad Zulfikar Trysnawan; Hendik Eko H.S; Dimas Okky Anggriawan
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.
Inrush Current Based on Fast Fourier Transform Mochamad Ilham Zamzami; Eka Prasetyono; Dimas Okky Anggriawan; Mike Yuliana
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.