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All Journal International Journal of Electrical and Computer Engineering Rotasi ELKHA : Jurnal Teknik Elektro Mechatronics, Electrical Power, and Vehicular Technology TELKOMNIKA (Telecommunication Computing Electronics and Control) ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika EMITTER International Journal of Engineering Technology JURNAL NASIONAL TEKNIK ELEKTRO INVOTEK: Jurnal Inovasi Vokasional dan Teknologi Techne : Jurnal Ilmiah Elektroteknika JAREE (Journal on Advanced Research in Electrical Engineering)
Mohammad Zaenal Efendi
Program Studi Teknik Elektro Industri, Departemen Teknik Elektro, Politeknik Elektronika Negeri Surabaya
Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Mechanical Engineering Transportation

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Balancing Charging System Using Adaptive Neuro-Fuzzy Inference System Based On CUK Converter Mohammad Fajar Setyawan; Mohammad Zaenal Efendi; Farid Dwi Murdianto
JAREE (Journal on Advanced Research in Electrical Engineering) Vol 5, No 2 (2021): October
Publisher : Department of Electrical Engineering ITS and FORTEI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/jaree.v5i2.199

Abstract

In a battery set, there is always a voltage difference caused by charging and discharging. Therefore, it is necessary to pay attention to the condition of the battery or State of Charge (SOC) so that it is in a balanced state between the batteries. Unbalanced battery conditions result in decreased performance of the battery. For that we need a balancing circuit that works actively with the help of a DC-DC converter. DC-DC converters generally have a principle like a buck-boost converter to increase and decrease the output voltage, however the output still has a fairly large ripple in the waveform. Therefore, the CUK converter is used which is a development of the buck-boost converter topology, where the output of this CUK converter has smaller ripples because it uses two capacitors and two inductors. Of the various methods used to adjust the duty cycle of the CUK converter, a precise and accurate algorithm is needed to overcome the instability of the converter output. The method used to adjust the duty cycle uses the Adaptive Neuro-Fuzzy Inference System (ANFIS) algorithm as the development of the Fuzzy method. The system is implemented using MATLAB Simulink software. The simulation results show that the output of the CUK converter with the ANFIS method has a faster response speed reaching a set point of 1.95 × 10-4 seconds and the accuracy of the output voltage with ANFIS is 99.94% while the accuracy of the output converter current using ANFIS is 65.7%.Keywords: ANFIS, balancing, battery, CUK converter, state of charge (SOC).15
CC-CV Controlled Fast Charging Using Fuzzy Type-2 for Battery Lithium-Ion Ahmad Zidan Falih; Mohammad Zaenal Efendi; Farid Dwi Murdianto
JAREE (Journal on Advanced Research in Electrical Engineering) Vol 5, No 2 (2021): October
Publisher : Department of Electrical Engineering ITS and FORTEI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/jaree.v5i2.200

Abstract

Energy dependency is increasing along with the increase in population growth rate, while the fossil energy is decreasing. Alternative energy such as solar energy is one solution to provide renewable energy, but solar energy cannot provide an intense supply of energy. Therefore, the equipment needs an energy storage. The battery has important role in energy storage with the performance of the battery that need an attention. The method and type of battery used  must be considered to maintain battery lifetime and  reduce overcharging. The purpose of this research is to understand the process of fast charging the CC-CV (Constant Current Constant Voltage) method on Lithium-Ion battery which is expected to reduce battery overcharging. In this method, the current is maintained constant until certain conditions then followed by constant voltage to prevent overcharging. The voltage from the solar panel is very high, voltage reduction is needed as the charging voltage for the battery. The DC-DC Converter used is Buck Converter which is given Fuzzy Type-2 algorithm to maintain a current of 10 Ampere during CC conditions and  a voltage of 14.4 Volt during CV conditions with switch of CC conditions to CV conditions on SoC 99.25%.Keywords: battery charging, buck converter, CC-CV, lithium-ion, type-2 fuzzy.
Prototipe Power Supply Gate driver untuk Multilevel Inverter dengan Menggunakan Flyback Converter Multi Output Novie Ayub Windarko; Akhmad Puryanto; Rachma Prilian Eviningsih; Moh. Zaenal Efendi; Eka Prasetyono; Bambang Sumantri
Techné : Jurnal Ilmiah Elektroteknika Vol. 19 No. 1 (2020)
Publisher : Fakultas Teknik Elektronika dan Komputer Universitas Kristen Satya Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1110.657 KB) | DOI: 10.31358/techne.v19i01.219

Abstract

Dengan perkembangan konverter elektronika daya, kebutuhan untuk memperkecil ukuran dan keandalan semakin meningkat. Dengan meningkatnya frekuensi switching pada konverter, maka dv/dt yang tinggi dapat menyebabkan kesalahan dalam turn-on ataupun turn-off switching devices. Masalah-masalah tersebut dapat diatasi dengan menerapkan tegangan bias negatif untuk melakukan turn-off switching devices. Makalah ini mengusulkan prototipe power supply gate driver yang dikhususkan untuk Multi Level Inverter (MLI). Sebuah prototipe power supply gate driver yang menggunakan satu unit konverter flyback dengan multi output untuk tegangan bias positif dan negatif, serta terisolasi galvanis sebanyak switching devices MLI. Dengan menggunakan topologi dasar flyback maka konverter ini memiliki isolasi galvanis melalui trafo frekuensi tinggi. Dari hasil eksperimen proses switching bisa berubah dari kondisi dari on menuju off dan dari off menuju on bisa berjalan secara sempurna.
Hybrid photovoltaic maximum power point tracking of Seagull optimizer and modified perturb and observe for complex partial shading Novie Ayub Windarko; Evi Nafiatus Sholikhah; Muhammad Nizar Habibi; Eka Prasetyono; Bambang Sumantri; Moh. Zaenal Efendi; Hazlie Mokhlis
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 5: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i5.pp4571-4585

Abstract

Due to natural randomness, partial shading conditions (PSCs) to photovoltaic (PV) power generation significantly drop the power generation. Metaheuristic based maximum power point tracking (MPPT) can handle PSCs by searching PV panels’ global maximum power point (GMPP). However, trapped at local maxima, sluggishness, continuous power oscillations around GMPP and inaccuracy are the main disadvantages of metaheuristic algorithm. Therefore, the development of algorithm under complex PSCs has been continuously attracting many researchers to yield more satisfying results. In this paper, several algorithms including conventional and metaheuristic are selected for candidate, such as perturb and observe (P&O), firefly (FF), differential evolution (DE), grey wolf optimizer (GWO) and Seagull optimizer (SO). From the preliminary study, SO has shown best performance among other candidates. Then, SO is improved for rapid global optimizer. Modified variable step sizes perturb and observe (MVSPO) is applied to enhance the accuracy tracking of SO. To evaluate the performances, high complexity multipeak partial shading is used to test the algorithms. Statistical results are also provided to analyze the trend of performances. The proposed method performances are shown better fast-tracking time and settling time, high accuracy, higher energy harvesting and low steady-state oscillations than other candidates.
Perbandingan Performa Metode Maximum Power Point Tracking Human Psychology Optimization (HPO), Artificial Bee Colony (ABC) dan Fuzzy Logic Controller (FLC) pada Flyback Converter Kondisi Parsial Shading Moh. Zaenal Efendi; Mochammad Rody Dwirantono; Suhariningsih Suhariningsih; Lucky Raharja
JURNAL NASIONAL TEKNIK ELEKTRO Vol 12, No 2: July 2023
Publisher : Jurusan Teknik Elektro Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jnte.v12n2.1022.2023

Abstract

Maximum Power Point Tracking (MPPT) is a method to track the power point of an energy source with the intention to generate maximum power. The surface of the Solar Panel has the possibility of being blocked when it receives sunlight. The barrier can be in the shape of shadows of objects that are nearby solar panels. The problem causes the power generated to be not optimal and makes more than one MPPT peak on the characteristics of P-V. This paper compares several methods of MPPT such as Human Psychology Optimization (HPO), Artificial Bee Colony (ABC), and Fuzzy logic Controller (FLC) under partial shading conditions, the comparison of three method by simulation. This algorithm hooks up to a flyback converter to provide MPP. From the results of MPPT accuracy in partial shading situations, the ABC and HPO approach methods can achieve GMPP with more than 82.22 % accuracy. For convergence, ABC needs extra time to discover GMPP. From the results, the Fuzzy approach can track however nevertheless trapped on LMPP.
Improvisasi Metode Biseksi pada Maximum Power Point Tracking (MPPT) dengan Menggunakan Algoritma Incremental Conductance Habibi, Muhammad Nizar; Windarko, Novie Ayub; Efendi, Moh. Zaenal; Eviningsih, Rachma Prilian; Mahendra, Luki Septya; Junianto, Sony
ROTASI Vol 26, No 1 (2024): VOLUME 26, NOMOR 1, JANUARI 2024
Publisher : Departemen Teknik Mesin, Fakultas Teknik, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/rotasi.26.1.52-61

Abstract

The solar energy potential reaches 207.8 GWp in Indonesia, providing numerous opportunities to harness renewable energy. One approach is utilizing solar panels; however, these panels have a low energy conversion rate. Maximum Power Point Tracking (MPPT) is a technique that can maximize the performance of solar panels to consistently generate maximum power. Bisection MPPT is implemented in the system due to its ease of implementation, but it performs less effectively under low irradiance. The Incremental Conductance algorithm is a suitable choice for improving Bisection MPPT. Apart from being easy to implement, the Incremental Conductance algorithm is not dependent on the characteristics of the solar panel. It also features Variable Step Size to eliminate ripple when reaching the maximum power of the solar panel. Incremental Conductance MPPT can enhance Bisection MPPT with a maximum increase of 17,483 Watts. The Bisection-Incremental Conductance MPPT algorithm takes 2.122 seconds to reach the maximum power of the solar panel, generating 1.89 x 10^6 Ws of energy for 0.4 seconds. It yields the highest value compared to Bisection MPPT and Incremental Conductance MPPT.
Maximum Power Point Tracking dengan Metode Modified Human Psychology Optimization pada Kondisi Partial Shading EFENDI, MOH. ZAENAL; RAHARJA, LUCKY PRADIGTA SETIYA; DWIRANTONO, MOCHAMMAD RODY; ARSANDI, FEBY CHANDRA; LUTFIAH, NABILA
ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika Vol 10, No 4: Published October 2022
Publisher : Institut Teknologi Nasional, Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26760/elkomika.v10i4.976

Abstract

ABSTRAKPanel surya memiliki kemungkinan tertutup saat menerima sinar matahari sehingga terjadi kondisi partial shading yang berpengaruh pada daya panel surya. Kita dapat memaksimalkan daya keluaran panel surya dengan Metode Maximum Power Point Tracking (MPPT). MPPT konvensional memiliki kemungkinan terjebak pada kondisi Local Peak (LP) sehingga daya yang dihasilkan tidak maksimal. Untuk mengatasi hal itu digunakan metode Modified Human Psychology Optimization (MHPO) pada kondisi partial shading sehingga MPPT dapat mencapai Global Peak (GP). Metode MHPO diterapkan pada Flyback Converter untuk melihat performansinya. Metode MHPO memiliki akurasi rata-rata di atas 98,75% dan waktu tracking yaitu 0,29 detik. Metode MHPO dapat mencapai kenaikan daya maksimum mencapai 45,57% dibandingkan dengan metode Human Psychology Optimization (HPO). Dengan metode MHPO dapat meningkatkan hasil keluaran daya panel surya pada kondisi partial shading.Kata kunci: Panel Surya; Partial Shading; MPPT; MHPO; Flyback Converter. ABSTRACTSolar panels have the possibility of being closed when receiving sunlight so that partial shading conditions occur which affect the power of the solar panels. We can maximize the output power of solar panels with the Maximum Power Point Tracking (MPPT) Method. Conventional MPPT has the possibility of being trapped in the Local Peak (LP) condition so that the power generated is not optimal. To overcome this problem, the Modified Human Psychology Optimization (MHPO) method is used in partial shading conditions so that MPPT can reach Global Peak (GP). The MHPO method is applied to the Flyback Converter to see its performance. The MHPO method has an average accuracy of over 98.75% and a tracking time of 0.29 seconds. The MHPO method can achieve a maximum power increase of 45.57% compared to the Human Psychology Optimization (HPO) method. The MHPO method can increase the output power of solar panels in partial shading conditions.Keywords: Solar Panels; Partial Shading; MPPT; MHPO; Flyback Converter.
A Comparison of Type-1 and Type-2 Fuzzy Logic Controller for Full Bridge Boost Converter on DC Microgrid System EFENDI, MOH. ZAENAL; ROMADLONIYAH, NUR SHINTA; EVININGSIH, RACHMA PRILIAN; WINDARKO, NOVIE AYUB
ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika Vol 11, No 4: Published October 2023
Publisher : Institut Teknologi Nasional, Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26760/elkomika.v11i4.1046

Abstract

ABSTRAKDengan meningkatnya kebutuhan listrik, penurunan pasokan energi fosil, serta sulitnya pendistribusian listrik ke daerah terpencil merupakan beberapa masalah yang mendesak. Energi matahari melalui panel surya dapat digunakan untuk mendukung sistem DC Microgrid serta cocok untuk jaringan listrik skala kecil. Full Bridge Boost Converter dengan transformator frekuensi tinggi yang dikendalikan oleh Fuzzy Logic Type-1 (T1FL) dan Fuzzy Logic Type-2 (T2FL) merupakan salah satu pilihan yang dapat dilakukan untuk memaksimalkan pemanfaatan energi matahari sehingga dapat meningkatkan efisiensi serta keandalan sistem pada DC Microgrid dengan menjaga tegangan keluaran menjadi konstan. Dari hasil pengujian dapat diketahui bahwa dengan menggunakan T2FL dapat menjaga tegangan keluaran Full Bridge Boost Converter dapat mencapai tegangan setpoint 320V dengan kesalahan sebesar 0.16% dan stabil dalam 0.59742ms. Sementara, T1FL memerlukan 0.7161ms untuk mencapai setpoint dengan kesalahan 2.8%.Kata kunci: full bridge boost converter, T2FL, T1FL, DC Microgrid ABSTRACTThe increasing electricity demand, the decreasing supply of fossil energy, and the difficulty in distributing electricity to remote areas are some of the urgent problems. Solar energy through solar panels can be used to support DC Microgrid systems and is suitable for small-scale power grids. Full Bridge Boost Converter with high-frequency transformers controlled by Fuzzy Logic Type-1 (T1FL) and Fuzzy Logic Type-2 (T2FL) is one of the choices that can be made to maximize the use of solar energy to increase the efficiency and reliability of systems on DC Microgrids by keeping the output voltage constant. From the test results, it can be seen that using T2FL can maintain the output voltage of the Full Bridge Boost Converter which can reach a setpoint voltage of 320V with an error of 0.16% and is stable within 0.59742ms. Meanwhile, T1FL takes 0.7161ms to reach the setpoint with an error of 2.8%.Keywords: full bridge boost converter, T2FL, T1FL, DC Microgrid
Paralel Flyback Converter sebagai PFC pada Lampu LED menggunakan Fuzzy Type-2 EFENDI, MOH. ZAENAL; WATI, DEWI KUSUMA; RAHARJA, LUCKY PRADIGTA SETIYA
ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika Vol 9, No 4: Published October 2021
Publisher : Institut Teknologi Nasional, Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26760/elkomika.v9i4.938

Abstract

ABSTRAKPeralatan elektronika umumnya memerlukan catu daya berupa sumber tegangan DC yang berasal dari sumber tegangan AC 220 V yang disearahkan menggunakan penyearah gelombang penuh. Pemasangan filter kapasitor pada sisi output penyearah menyebabkan bentuk gelombang arus masukan terdistorsi sehingga menimbulkan arus harmonisa yang mengakibatkan nilai faktor daya menjadi rendah. Artikel ini membahas mengenai paralel flyback konverter sebagai PFC (Power Factor Correction) pada lampu LED 36 V/60 W menggunakan algoritma fuzzy type-2. Flyback konverter pertama sebagai regulator tegangan DC bekerja dalam kondisi CCM (Continuous Conduction Mode). Flyback konverter kedua sebagai PFC bekerja dalam kondisi DCM (Discontinuous Conduction Mode) sehingga konverter bersifat resistif. Hasil simulasi menunjukkan bahwa paralel flyback konverter dapat memperbaiki faktor daya dari 0.597 menjadi 0.903 dan dapat menjaga tegangan keluaran konstan sebesar 36 V menggunakan algoritma fuzzy type-2 serta arus input yang dihasilkan memenuhi standar internasional hamonisa IEC61000-3-2 kelas C.Kata kunci: PFC, flyback konverter, IEC61000-3-2, lampu LED, fuzzy type-2 ABSTRACTElectronic equipment generally requires a DC voltage source that comes from a rectified 220 AC voltage source using full-wave rectifier. Installing capacitor filter on the output of rectifier makes the input current waveform becoming distorted that cause harmonic current which results in low power factor value. This article discusses parallel flyback converter as PFC (Power Factor Correction) on 36 V/60 W LED lamp using fuzzy type-2 algorithm. The first flyback converter as voltage dc regulator works in CCM (Continuous Conduction Mode). The second flyback converter as PFC works in DCM (Discontinuous Conduction Mode) to make the resistive converter. The simulation results shows the parallel flyback converter can improve the power factor from 0.597 to become 0.903 and can maintain a constant output voltage of 36 V using fuzzy type-2 algorithm and the input current meets the international harmonics standard of IEC61000-3-2 class C.Keywords: PFC, flyback converter, IEC61000-3-2, LED lamp, fuzzy type-2
Temperature and Humidity Control System for 20 kV of Cubicle with Multiple Input Multiple Output Fuzzy Logic Controller Ramadhan, Mochammad Berliano Putra; Efendi, Moh. Zaenal; Nugraha, Syechu Dwitya
JAREE (Journal on Advanced Research in Electrical Engineering) Vol 7, No 2 (2023): July
Publisher : Department of Electrical Engineering ITS and FORTEI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/jaree.v7i2.367

Abstract

Cubicle 20 kV is a crucial electrical equipment in the 20 kV power distribution system. Often, cubicle issues arise due to excessively low or high temperatures and humidity, which can lead to the presence of water spots and corrosion on the components inside the 20 kV cubicle. One of the efforts to maintain the reliability of this 20 kV cubicle is to ensure that the temperature and humidity inside the cubicle remain within their operational limits. To achieve this, a system is needed to control the temperature and humidity in the 20 kV cubicle. The system can monitor and control the temperature and humidity inside the cubicle by adjusting the activation angle of the exhaust fan and heater. Control is achieved using a multiple-input, multiple-output fuzzy logic controller. The main components of this system are the STM32 microcontroller, DHT22 sensor, and ESP8266 module for monitoring temperature and humidity via a website. System has successfully controlled temperature and humidity d with a set point value of 35 °C and humidity of  60% RH. This implementation of fuzzy multiple input multiple outputs has performed well and resulted in only a small error of 0.55% for temperature and 1.05% for humidity.With the presence of this device, the temperature and humidity in the cubicle 20 kV can be controlled, and it enables the PLN operator to easily monitor and maintain the cubicle 20 kV.
Co-Authors Abdul Rizal Abdul Rizal, Abdul Ahmad Firyal Adila Ahmad Zidan Falih Ahmad, Mirza Ghulam Akhmad Puryanto Aldi Erzanuari Aldi Erzanuari, Aldi Annas Budi Prastyawan ARSANDI, FEBY CHANDRA Bambang Sumantri DWIRANTONO, MOCHAMMAD RODY Eka Prasetyono, Eka Evi Nafiatus Sholikhah Farid Dwi Murdianto Fito Ardli Fitri Habibi, Muhammad Nizar Hazlie Mokhlis Lucky Pradigta Setiya Raharja Lucky Raharja Luki Septya Mahendra Luluk Badriyah Lutfiah, Nabila MOCHAMMAD RODY DWIRANTONO Moh. Faisal Amir Moh. Faisal Amir Moh. Ifaldi Akbar Mohammad Fajar Setyawan Novie Ayub Windarko Nugraha, Syechu Dwitya Prakoso, Rifqi Noviantono Rachma Prilian Eviningsih Rachma Prilian Eviningsih, Rachma Prilian Ramadhan, Mochammad Berliano Putra Romadloniyah, Nur Shinta Sony Junianto Suhariningsih Suhariningsih Suryono . Suryono Suryono Syechu Dwitya Nugraha Taufik Hidayat WATI, DEWI KUSUMA Wicaksana, Ragil Wigas