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All Journal Community Development Journal: Jurnal Pengabdian Masyarakat Joule (Journal of Electrical Engineering) Jurnal Pengabdian Masyarakat Bhinneka Jurnal Mosfet Jurnal Teknologi Manufaktur dan Industri
Mustafa, Syahrul
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Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Health Professions Industrial & Manufacturing Engineering Mechanical Engineering Public Health

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Journal : Jurnal Mosfet

 1 
Implementasi Novel Bat Algorithm Untuk Penjadwalan Ekonomis Pembangkit Listrik Termal Dengan Integrasi PLTB Nur Fitri, Sulistianingsih; Mustafa, Syahrul; Azis, Fatmawati
Jurnal Mosfet Vol. 4 No. 2 (2024): 2024
Publisher : Fakultas Teknik Universitas Muhammadiyah Parepare (FT-UMPAR)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31850/jmosfet.v4i2.3148

Abstract

Economic dispatch aims to control the variables of the power system so that the power plants can generate maximally based on load demand according to the characteristics of each plant and with cheaper production costs. In this study, economic dispatch is applied to thermal power plants with the integration of Wind Power Plants (PLTB) in Sulselrabar 150kV power system using the Novel Bat Algorithm (NBA) optimization method, considering voltage stability. The generation cost that can be reduced using the NBA method is IDR 12,583,781 per hour compared to the results of the existing system. With the integration of 100% of the PLTB capacity, the NBA method still provides cheaper economic dispatch results. Using the NBA method, the generation cost can be reduced by IDR 29,854,367 compared to the results of the existing system. After the integration of 100% of the PLTB capacity, the power losses obtained are smaller than before the integration of the PLTB. The system bus voltage conditions before and after the integration of the PLTB are also in good condition as they are within the voltage regulation limits set by PLN, which are +5% and -10%
Pengembangan PLTMH dengan Model Multipowerhouse (MPH) untuk Optimalisasi Air Buangan Turbin PLTMH Garassik di Sungai Garassik Kab. Enrekang Muhammad Khaidir; Rahman, Fadhli; Mustafa, Syahrul
Jurnal Mosfet Vol. 5 No. 1 (2025): 2025
Publisher : Fakultas Teknik Universitas Muhammadiyah Parepare (FT-UMPAR)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31850/jmosfet.v5i1.3510

Abstract

The Garassik Micro-Hydro Power Plant in Panassang Village, Enrekang Regency, with an installed capacity of 3.7 kW, experiences an energy deficit due to the community's electricity demand of 390.74 kWh per day. Despite its efficient operation, the plant generates a maximum of only 88.8 kWh per day, underscoring the need for capacity enhancement. This study explores the potential of utilizing turbine wastewater as an energy source by designing a Multi Powerhouse (MPH) Micro-Hydro Power Plant to optimize water energy usage. The proposed MPH system evaluates water energy potential, determines optimal powerhouse placements for effective head height, and calculates total power output. Unlike the single-powerhouse model, the MPH system addresses water flow limitations, particularly during periods of reduced flow, significantly improving total power output to 160.235 kW, a 171% increase. Key advantages of the MPH model include better utilization of turbine wastewater, enhanced operational flexibility, and improved water energy efficiency. Using a descriptive quantitative research method, this study begins with a location survey to collect turbine wastewater characteristics, followed by mathematical modeling for analysis. Results reveal output flow rates of 0.189 m³/s, 0.187 m³/s, and 0.185 m³/s across three powerhouses, with effective head heights of 24.782 m, 29.725 m, and 34.729 m, respectively. The system uses Crossflow turbines, ideal for medium heads and moderate flow rates. Economic analysis indicates an NPV of IDR 2.400.000.000,- an IRR of 14%, and a BCR of 2.5, with a payback period of 5.45 years, making the project financially viable and sustainable.
Optimasi Peramalan Beban Listrik dengan Regresi Linear Berganda Berbasis Algoritma Genetika: Studi Kasus Kabupaten Soppeng Khaidir, Muhammad; Karim, Saktiani; Rahman N, Muhammad Fathur; Mustafa, Syahrul; Virgiawan, Reihan
Jurnal Mosfet Vol. 5 No. 2 (2025): 2025
Publisher : Fakultas Teknik Universitas Muhammadiyah Parepare (FT-UMPAR)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31850/jmosfet.v5i2.4024

Abstract

Electricity is a crucial infrastructure supporting economic and social development, thus requiring reliable supply planning. In Soppeng Regency, historical data from 2019–2023 show population growth from 226,992 to 240,955 people and GRDP increase from 10,938 to 14,909 billion rupiah, driving higher electricity demand. Customer numbers rose in the household sector from 29,438 to 34,376 and in industry from 33 to 58, with similar upward trends in connected load and energy use. This study addresses the challenge of accurate forecasting by applying Multiple Linear Regression (MLR) optimized with Genetic Algorithm (GA). Forecasting results up to 2028 predict household customers reaching 40,449 and industrial customers 89, while connected load grows from 35.7 to 34.0 million VA in households and from 8.6 to 17.4 million VA in industry. Electricity consumption is projected to exceed 41.8 million kWh in households and 13.5 million kWh in industry by 2028. Model evaluation using Mean Absolute Percentage Error (MAPE) confirms reliable accuracy, making the MLR–GA approach effective for future capacity planning.
Co-Authors Andi Fitriati Aswad Alfian M, Moh. Chandra, Muhammad Ali Fachrul, Muhammad Fatmawati Azis, Fatmawati Irvawansyah, Irvawansyah Karim, Saktiani Khaidir, Muhammad Kido, Muh Ikram Muhammad Ikhsan Muhammad Ikhsan Muhammad Khaidir Mukhlisin Mukhlisin Nur Fitri, Sulistianingsih Parawangsa, Akbar Naro Rahman N, Muhammad Fathur Rahman, Fadhli Rasmondo, Rasmondo Umar Muhammad Virgiawan, Reihan