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All Journal Elektrika Borneo JTEIN: Jurnal Teknik Elektro Indonesia Eduvest - Journal of Universal Studies
Syamsir Abduh
Institut Teknologi PLN
Aerospace Engineering Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Energy Engineering Health Professions Industrial & Manufacturing Engineering Neuroscience Social Sciences

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Optimization Of Cogging Torque in 28-Pole 24-Slot Permanent Magnet Generator Zacky Irfan Al Farisie; Tajuddin Nur; Marwan Rosyadi; Syamsir Abduh
Eduvest - Journal of Universal Studies Vol. 6 No. 4 (2026): Eduvest - Journal of Universal Studies
Publisher : Green Publisher Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59188/eduvest.v6i4.52888

Abstract

This study addresses the growing demand for efficient renewable energy conversion systems, particularly in low- to medium-wind-speed regions such as Indonesia, where wind resources typically range between 4–6 m/s. Permanent magnet generators (PMGs) are widely used in wind power plants due to their high efficiency and simple structure; however, their performance is often limited by cogging torque, which causes rotational resistance, vibration, and reduced energy conversion efficiency. This research aims to analyze and optimize the reduction of cogging torque in a 28-pole, 24-slot permanent magnet generator through geometric modification techniques. The study employs a quantitative simulation approach using FEMM 4.2 software and LUA 4.0 scripting to model magnetic flux distribution and torque characteristics. The optimization process includes variations in air gap widening, magnet edge shaping, slot opening adjustment, and the addition of dummy slots. The initial design produced a cogging torque of 0.00498 Nm. After the first optimization stage, the value decreased to 0.00028 Nm, while the second optimization achieved a significant reduction to 0.00005 Nm, corresponding to a 98.99% decrease. The results demonstrate that combining magnet edge shaping with dummy slots is highly effective in minimizing cogging torque and improving flux uniformity. In conclusion, the optimized design enhances generator performance, particularly in low-speed wind applications, making it a promising solution for sustainable energy development.
Transformer Load Calculator & Simulator for 70kV Seduduk Putih Substation: Statistical Analysis and Prediction Nur Aldillah Julita; Syamsir Abduh; Farid Wijaya
Jurnal Teknik Elektro Indonesia Vol 7 No 1 (2026): JTEIN: Jurnal Teknik Elektro Indonesia
Publisher : Departemen Teknik Elektro Fakultas Teknik Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/jtein.v7i1.790

Abstract

This study aimed to analyze the load patterns of two power transformers at the 70kV Seduduk Putih Substation using descriptive statistical approaches, load analysis, and Multiple Linear Regression based on hourly data throughout 2024. The analysis focused on two main transformers with a capacity of 30 MVA each, employing descriptive statistics and regression methods to identify distribution, trends, and relationships between variables. The results indicate that the average load of the two transformers at the 70kV Seduduk Putih Substation is as follows: Transformer 1 operates at 60% of its maximum load, while Transformer 2 operates at 45% of its maximum load. This suggests that the average loads of both transformers remain below 80%, which is considered normal/safe. However, the peak load analysis shows that Transformer 1 reaches a maximum load of 92.08%, and Transformer 2 reaches 87.03%, indicating that their peak loads exceed 80%. Load data was collected periodically for specific periods, including hourly, monthly, and peak load measurements. Multiple Linear Regression was used to evaluate the relationship between time and transformer load. The findings reveal that the transformers exhibit distinct load patterns for each month, with a moderate correlation to time as indicated by the R-Square value. The peak load analysis identifies critical times with potential overloading risks. This study is expected to serve as a reference for PLN, the operator of the substation, in making operational decisions.
KAJIAN KELAYAKAN CONDITION BASE MAINTENANCE TERHADAP INTERVAL OVERHAUL TM2500 PT PLN BATAM Arif Budiman; Syamsir Abduh; Marwan Rosyadi
Elektrika Borneo Vol 12, No 1 (2026): Elektrika Borneo Edisi April
Publisher : Jurusan Teknik Elektro, Fakultas Teknik, Universitas Borneo Tarakan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35334/eb.v12i1.7267

Abstract

Inefisiensi biaya operasional akibat ketidakselarasan strategi pemeliharaan dengan degradasi aktual aset menjadi tantangan kritikal pada turbin gas aero-derivatif di sistem isolated grid. Praktik konvensional Time-Based Maintenance (TBM) yang memberlakukan interval overhaul kaku setiap 12.500 jam sering kali memicu over-maintenance, karena mengabaikan variabilitas kondisi termodinamika dan integritas mekanikal mesin. Penelitian ini mengusulkan transisi strategis menuju Condition-Based Maintenance (CBM) melalui pengembangan "Algoritma Gatekeeper" yang mengintegrasikan parameter termodinamika kritis (T48, PS3) dengan validasi visual langsung melalui Borescope Inspection (BSI). Pendekatan ini menempatkan data visual sebagai penentu akhir dalam keputusan ekonomi, memastikan keamanan teknis sebelum eksploitasi nilai ekonomi aset dilakukan. Melalui analisis tekno-ekonomi (Cost-Benefit Analysis) pada armada 20 unit TM2500 di PT PLN Batam, strategi ini terbukti mampu menghasilkan efisiensi signifikan. Hasil simulasi menunjukkan potensi penghematan biaya langsung sebesar USD 5.614.431 per tahun dengan nilai Benefit-Cost Ratio (BCR) mencapai 2,36. Temuan ini mengimplikasikan bahwa integrasi BSI dalam kerangka CBM bukan hanya meningkatkan reliabilitas, tetapi juga menetapkan standar manajemen aset baru yang adaptif dan efisien secara finansial.
Co-Authors Arif Budiman Farid Wijaya Marwan Rosyadi Nur Aldillah Julita Tajuddin Nur Zacky Irfan Al Farisie