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Design and Simulation of Utilization of Solar Cells as Battery Chargers CC-CV (Constant Current-Constant Voltage) Method with Fuzzy Control Indhana Sudiharto; Endro Wahjono; Lugiana Nur Fitriah Rhamadani Lugiana
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 7, No. 2, May 2022
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v7i2.1448

In a country with a tropical climate, the use of the sunlight is very important. Thus, to be able to apply, a solar power conversion system is needed into a source of electrical energy. The use of electrical equipment that is quite high will increase the consumption of electrical power so that people spend more and more on electricity costs. A battery is a device consisting of electrochemical cells that can store electrical energy. Overcharging the battery causes the battery to be susceptible to damage. So that the process of charging the battery becomes important, to get maximum attention and good efficiency. In this study, the use of solar cells with battery chargers using the CC-CV (Constant Current-Constant Voltage) Fuzzy Control method uses a solar cell to convert sunlight into electrical energy. The specifications of the solar cell used are 100 WP, while the charging process uses a DC-DC Sepic Converter. DC-DC Sepic Converter can increase efficiency and output polarity that is not reversed. This system is used to charge the lead-acid battery of 12 Volt 20 Ah. The charging method used is constant current-constant voltage (CC-CV) using Fuzzy Logic Control to adjust the duty cycle so that the converter output is by the constant current - constant voltage (CC-CV) planning. The constant current - constant voltage (CC-CV) method was chosen because it can provide good efficiency in charging time and the addition of the Constant Voltage method after Constant Current is enabled to keep the voltage at the setpoint and avoid overvoltage during the charging process. Sepic Converter is used to maintain the value of the voltage set point at 14.4 Volts and 6 Ampere for battery charging current.

BLDC Motor Drives with A Programmable Simplified C-Block to Generate Accurate Six-Step PWM Based on STM32 Microcontroller Muhammad Rizani Rusli; Mentari Putri Jati; Mochamad Ari Bagus Nugroho; Ony Asrarul Qudsi; Indhana Sudiharto; Farid Dwi Murdianto; Endro Wahjono
Elinvo (Electronics, Informatics, and Vocational Education) Vol 7, No 2 (2022): November 2022
Publisher : Department of Electronic and Informatic Engineering Education, Faculty of Engineering, UNY

This paper presents a digital implementation of a brushless direct current motor (BLDCM) drive with a six-step pulse width modulation (PWM) using a programmable simplified C-block based on the STM32 microcontroller. The implementation is conducted through the PSIM simulation platform, which is commonly used for power electronics and motor control. This approach combines the benefits of using a programmable simplified C-block for precise and flexible programming with the PWM concepts of the STM32 microcontroller. The PWM method used on the BLDCM drive is the unipolar upper PWM technique (H~PWM_L~ON). The performance of the PWM implementation is analyzed in detail, including the accuracy of the PWM generation using a Fast Fourier Transform (FFT), the gating of the IGBTs in the three-phase inverter, and the effect of the duty cycle on the BLDCM's speed, phase voltage, and phase current.

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

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 %.

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

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 %

Implementation smart charging technique using particle swarm optimization to achieve best performance charger Indhana Sudiharto; Farid Dwi Murdianto; Lavia Isnani
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 14, No 3: September 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijpeds.v14.i3.pp1604-1614

These days, there are an increasing number of electronic devices that use batteries as their energy source, often known as portable electronic devices. However, the battery may run out of energy and a recharging process is required to keep the electronic device functional. A charger that is in accordance with the battery specifications is required to complete the charging process. Incompatible chargers can overcharge batteries and shorten their lifetime. Since there are many different types of electronic devices, many different chargers are required, especially since most chargers on the market are static and can only be used with one kind of electronic device. This will increase the costs that customers must pay, especially those who have many types of electronic devices. As a result, this research will create a smart charger using the PSO algorithm that can be used to complete the charging process on all types of portable electronic devices. To test smart chargers, five different battery types from electronic devices with different specifications are used. From the test result, the smart charger can charge five different types of battery loads with various specifications with 100% accuracy at a speed that takes 50.4 seconds to reach a steady state.

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

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

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 %.

Shunt Active Power Filter untuk Meredam Harmonisa Beban Non-Linear Satu Fasa Fahmi Naufala Mumtaz; Indhana Sudiharto; Ony Qudsi
Electrician : Jurnal Rekayasa dan Teknologi Elektro Vol. 16 No. 1 (2022)
Publisher : Department of Electrical Engineering, Faculty of Engineering, Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar

Penggunaan beban non-linear semakin umum digunakan seiring berkembangnya teknologi yang menerapkan komponen elektronika daya di dalamnya. Beban non-linear dapat menimbulkan harmonisa pada jaringan listrik dan mengakibatkan penurunan kualitas daya. Cara yang dapat digunakan untuk mengatasi permasalahan ini salah satunya adalah dengan menggunakan Active Power Filter. Pada penelitian ini suatu Shunt Active Power Filter (SAPF) untuk sistem satu fasa didesain dan disimulasikan untuk meredam harmonisa yang timbul karena penggunaan beban non-linear satu fasa yang sering digunakan di skala rumah tangga. Teori ip-iq dan kontrol PI untuk tegangan DC digunakan untuk mendapatkan referensi arus kompensasi. Pada simulasi, beban yang digunakan berupa penyearah dioda yang dihubungkan ke beban RL seri. Hasil simulasi menunjukkan bahwa sebelum pemasangan SAPF, nilai THD arus sumber mencapai 32.63 persen. Sedangkan setelah pemasangan SAPF nilai THD arus sumber yang dihasilkan hanya sebesar 4.47 persen. SAPF yang disimulasikan memiliki kemampuan peredaman harmonisa sebesar 28.16 persen dan dapat memenuhi standar yang ditoleransi oleh IEEE 519-2014.

Sistem Penyimpanan Energi Listrik Panel Surya untuk PJU dan Edukasi Masyarakat Desa Kembangbelor Luki Septya Mahendra; Indhana Sudiharto; Eka Prasetyono; Diah Septi Yanaratri; Rachma Prilian Eviningsih; Arman Jaya; Epyk Sunarno; Hendik Eko H Suharyanto; Muhammad Nizar Habibi; Muhammad Rizani Rusli; Ahmad Firyal Adila; Imam Dui Agusalim
BUDIMAS : JURNAL PENGABDIAN MASYARAKAT Vol 5, No 2 (2023): BUDIMAS : Jurnal Pengabdian Masyarakat
Publisher : LPPM ITB AAS Indonesia Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29040/budimas.v5i2.10967

Pembangunan kepariwisataan dikembangkan dengan pendekatan pertumbuhan, pemerataan ekonomi untuk kesejahteraan rakyat dan pembangunan yang berorientasi pada pengembangan wilayah, yang bertumpu kepada masyarakat dan bersifat memberdayakan masyarakat yang mencakupi berbagai aspek, seperti sumber daya manusia, pemasaran, destinasi, ilmu pengetahuan dan teknologi. Pada pengabdian ini melakukan pengambangan pariwisata pada aspek destinasi, ilmu pengetahuan dan teknologi. Dimana destinasi atau lokasi pada pengabdian di Dusun Paras, Desa Kembangbelor, Pacet, Mojokerto, Jawa Timur yang merupakan desa wisata edukasi. Desa ini memiliki program-program desa yang ingin mengembangkan pariwisata di aspek ilmu pengetahuan dan teknologi, maka digandenglah mitra Desa Kembangbelor khususnya Dusun Paras. Pembangunan sistem Pembangkit Listrik Tenaga Surya (PLTS) beserta penyimpanan energinya untuk dimanfaatkan sebagai penerangan jalan umum (PJU) dinilai cocok sebagai pengembangan pariwisata desa dalam aspek ilmu pengetahuan dan teknologi. Karena disisi lain mendapatkan kedua aspek tersebut, hal ini juga mendapatkan pemanfaatan energi terbarukannya untuk PJU jalan masuk desa yang belum ada penerangannya. Dengan adanya sistem yang dipasang masyarakat mendapat pemanfaatan energi PLTS untuk PJU dan tempat untuk belajar untuk wisata edukasi berupa ilmu pengetahuan dan teknologi mengenai energi terbarukan PLTS.

Real-Time Detection of Power Quality Disturbance Using Fast Fourier Transform and Adaptive Neuro-Fuzzy Inference System Ahmad Alvi Syahrin; Dimas Okky Anggriawan; Eka Prasetyono; Epyk Sunarno; Endro Wahjono; Indhana Sudiharto; 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.

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