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Pole-mounted Metering Circuit Breaker (PMCB) is a medium voltage protection device. Problems in the PMCB because operating at medium voltage causes insulation problems. The isolation problem that arises is due to partial discharge. Partial discharge can trigger the risk of flashover. In addition, corona discharge causes corrosion of the conductor, the effect is a failure and disconnection of electricity. This control system aims to maintain the temperature and humidity of the PMCB at the nominal values according to the standard. Based on SPLN D3.021-1:2020, it is known that under normal service conditions, the ambient air temperature does not exceed 40°C and the average temperature for 24 hours does not exceed 35°C and the highest relative humidity is 100% RH. The control system uses an AC voltage controller which is used to control the input voltage of the heater and exhaust fan so that the temperature and humidity can reach nominal operating conditions. The control method used is an artificial neural network (ANN) to find the ignition angle of the AC voltage controller as a TRIAC control. The test results using the ANN control method, system simulation produces a temperature error of 1.029% and humidity error of 2.48% and the hardware system produces a temperature error of 2.364% and humidity error of 8.673% compared to the set point temperature of 35°C and humidity of 50% RH. It can be concluded that the ANN control method can maintain the PMCB temperature and humidity according to standards

ABSTRAK Dengan 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  ABSTRACT The 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

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.

ABSTRAK Panel 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.  ABSTRACT Solar 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.

ABSTRAK Peralatan 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 ABSTRACT Electronic 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

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.

During its operation, a photovoltaic system may encounter many practical issues such as receiving uniform or non-uniform irradiance caused mainly by partial shading. Under uniform irradiance a photovoltaic panel has a single maximum power point. Conversely under non-uniform irradiance, a photovoltaic panel has several local maximum power points and a single global maximum power point. To maximize energy production, a maximum power point tracker algorithm is commonly implemented to achieve the maximum power operating point of the photovoltaic panel. However, the performance of the algorithm will depend on operating conditions such as variation in irradiance. Presently, most of existing maximum power point tracker algorithms work only in a single condition: either uniform or non-uniform irradiance. This paper proposes a new maximum power point tracker algorithm for photovoltaic power generation that is designed to work under uniform and partial shading irradiance conditions. Additionally, the proposed maximum power point tracker algorithm aims to provide: (1) a simple math algorithm to reduce computational load, (2) fast tracking by evaluating progress for every single executed duty cycle, (3) without random steps to prevent jumping duty cycle, and (4) smooth variable steps to increase accuracy. The performances of the proposed algorithm are evaluated by three conditions of uniform and partial shading irradiance where a targeted maximum power point is located: (1) far from, (2) near, and (3) laid between initial positions of particles. The simulation shows that the proposed algorithm successfully tracks the maximum power point by resulting in similar power values in those three conditions. The proposed algorithm could handle the partial shading condition by avoiding the local maxima power point and finding the global maxima power point. Comparisons of the proposed algorithm and other well-known algorithms such as differential evolution, firefly, particle swarm optimization, and grey wolf optimization are provided to show the superiority of the proposed algorithm. The results show the proposed algorithm has better performance by providing faster tracking, faster settling time, higher accuracy, minimum oscillation and jumping duty cycle, and higher energy harvesting.

The electrical energy generated by the photovoltaic (PV) as a renewable energy source highly affected by environmental conditions such as intensity of sunlight irradiance, temperature, geographic location and tilt angle of PV itself. How much power should be generated by the PV for every times and anywhere will be discussed in this paper. This paper are implemented models of clear sky solar irradiance, solar position and PV temperature to predict the power output should be generated by PV. The model is implemented on the ARM Cortex M4F microcontroller STM32F407 which is a 32bit microcontroller and equipped with DSP, so the prediction of PV power output can be done online and in real time. To be able to predict the PV power output online, at any time and wherever they are, in this study microcontroller equipped with temperature sensors and input geographical information (latitude-longitude) and also equipped with a memory card for data logger between the predictions and field measurement. Results have been obtained by field experiments, measurements test for PV is very close to predictions with an average error 4.72% and computation time for all models by microcontroller with DSP instruction 33.64% faster compare to without DSP instruction.

This paper presents a design and implementation of a converter which has a high power factor for battery charger application. The converter is a combination of a SEPIC converter and a full-bridge DC-DC converter connected in two stages of series circuit. The SEPIC converter works in discontinuous conduction mode and it serves as a power factor corrector so that the shape of input current waveform follows the shape of input voltage waveform. The full-bridge DC-DC converter serves as a regulator of output voltage and operates at continuous conduction mode. The experimental results show that the power factor of this converter system can be achieved up to 0.96.

This paper presents a combination of power factor correction converter using Flyback converter and Full-bridge dc-dc converter in series connection. Flyback converter is operated in discontinuous conduction mode so that it can serve as a power factor correction converter and meanwhile Full-bridge dc-dc converter is used for dc regulator. This converter system is designed to produce a 86 Volt of output voltage and 2 A of output current. Both simulation and experiment results show that the power factor of this converter achieves up to 0.99 and meets harmonic standard of IEC61000-3-2. Keywords: Flyback Converter, Full-bridge DC-DC Converter, Power Factor Correction.