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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) Journal of Electrical and Intelligent Systems (JEIS)
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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Temperature and Humidity Control System for Pole-Mounted Metering Circuit Breaker with Artificial Neural Network Methods Ahmad, Mirza Ghulam; Efendi, Moh. Zaenal; Eviningsih, Rachma Prilian
ELKHA : Jurnal Teknik Elektro Vol. 15 No.2 October 2023
Publisher : Faculty of Engineering, Universitas Tanjungpura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/elkha.v15i2.67933

Abstract

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
AC-DC PFC Converter Using Combination of Flyback Converter and Full-bridge DC-DC Converter Efendi, Moh. Zaenal; Rizal, Abdul; Erzanuari, Aldi; ., Suryono; Windarko, Novie Ayub
EMITTER International Journal of Engineering Technology Vol 2 No 1 (2014)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (6864.867 KB) | DOI: 10.24003/emitter.v2i1.21

Abstract

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.
Fractional tent map - chaotic horse herd optimization for global MPPT under partial shading conditions Rachma Prilian Eviningsih; Ewa Ari Irwansyah; Epyk Sunarno; Moh. Zaenal Efendi; Novie Ayub Windarko; Anggara Trisna Nugraha
Journal of Mechatronics, Electrical Power, and Vehicular Technology Vol 17, No 1 (2026)
Publisher : National Research and Innovation Agency

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55981/j.mev.2026.1423

Abstract

Photovoltaic efficiency is frequently compromised by physical obstructions, resulting in partial shading conditions. This non-uniform irradiance condition severely distorts system characteristics by inducing multiple power peaks. This study proposes a novel fractional tent map-chaotic horse herd optimization (FTM-CHHO) algorithm for global maximum power point (GMPP). By integrating fractional-order memory and chaotic maps, FTM-CHHO enhances global search capabilities and prevents entrapment in local maxima. The method was rigorously validated through simulations and hardware experiments using a SEPIC converter. Simulations demonstrated that FTM-CHHO achieved 99.52 % to 100 % tracking accuracy with rapid convergence times of 0.32 to 0.62 s. Furthermore, hardware tests under real-world shading confirmed its robustness, maintaining 95.54 % to 98.26 % accuracy and converging within 10.1 s. FTM-CHHO significantly outperformed perturb and observe (P8O) and standard horse herd optimization (HHO). These findings confirm that FTM-CHHO provides a highly reliable, fast, and efficient solution for maximizing solar energy extraction under complex environmental variability.
Experimental Validation of Enhanced Artificial Rabbit Optimization (ARO)-Based MPPT Method for Photovoltaic Systems Under Partial Shading Conditions Moh. Zaenal Efendi; Ircham Badrus Rahmadani; Muhammad Rizani Rusli
Journal of Electrical and Intelligent Systems Vol. 1 No. 1 (2026): April
Publisher : Politeknik Elektronika Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.68129/jeis.v1i1.33

Abstract

Partial shading often introduces multiple local maxima into the power–voltage (P-V) characteristics of photovoltaic (PV) systems, which makes conventional maximum power point tracking (MPPT) methods prone to converging to suboptimal operating points. To overcome this challenge, this study proposes an Enhanced Artificial Rabbit Optimization (ARO)-based MPPT method by incorporating a time-varying adaptive inertia-weight mechanism, enabling more accurate global maximum power point (GMPP) tracking under nonlinear irradiance conditions. The proposed method was experimentally validated on a laboratory-scale PV platform consisting of three series-connected PV modules, a SEPIC converter, and an STM32-based controller tested under four irradiance patterns. The GMPP reference values were determined through direct experimental P-V scanning. The experimental results indicate that the enhanced method consistently performed better than the conventional ARO baseline, achieving a maximum output power of 98.68 W with a tracking accuracy of 99.93%. Across all test cases, the extracted power and tracking accuracy improved by an average of 1.24% and 1.21%, respectively, without a noticeable increase in tracking time.
Co-Authors Abdul Rizal, Abdul Ahmad Firyal Adila Ahmad Zidan Falih Ahmad, Mirza Ghulam Akhmad Puryanto Aldi Erzanuari, Aldi Anggara Trisna Nugraha Annas Budi Prastyawan ARSANDI, FEBY CHANDRA Bambang Sumantri DWIRANTONO, MOCHAMMAD RODY Eka Prasetyono, Eka Epyk Sunarno Evi Nafiatus Sholikhah Ewa Ari Irwansyah Farid Dwi Murdianto Fito Ardli Fitri Habibi, Muhammad Nizar Hazlie Mokhlis Ircham Badrus Rahmadani 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 Rusli, Muhammad Rizani Sony Junianto Suhariningsih Suhariningsih Suryono . Syechu Dwitya Nugraha Taufik Hidayat WATI, DEWI KUSUMA Wicaksana, Ragil Wigas