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Journal : Jurnal Fortech

Desain Kontrol Pembangkit Listrik Tenaga Pikohidro Menggunakan PID-CES Berbasis Firefly Algorithm Anshoruddin, Ilham; Ali, Machrus; Rukslin, Rukslin; Nurohmah, Hidayatul
Jurnal FORTECH Vol. 5 No. 2 (2024): Jurnal FORTECH
Publisher : FORTEI (Forum Pendidikan Tinggi Teknik Elektro Indonesia)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56795/fortech.v5i2.5205

Abstract

Pembangkit Listrik Tenaga Pikohidro (PLTPH)  merupakan salah satu alternatif pembangkit listrik  kecil yang dapat digunakan untuk menggerakkan turbin yang mampu menghasilkan listrik. Permasalahan yang sering terjadi pada sistem pembangkit  Pikohidro adalah terjadinya ketidakstabilan frekuensi disebabkan oleh perubahan beban yang tersambung. Permasalahan ini dapat mengakibatkan kerusakan peralatan listrik. Oleh karena itu, diperlukan suatu teknologi untuk mengoptimalkan kinerja pembangkit listrik tenaga pikohidro, yaitu dengan menerapkan Load Frequency Control (LFC). Mekanisme LFC ini dirancang dengan menggunakan Proportional Integral Derivative (PID) dan Capacitive Energy Storage (CES). CES dapat digunakan untuk mempertahankan stabilitas frekuensi dalam jaringan listrik yang rentan terhadap fluktuasi, seperti jaringan yang terhubung dengan pembangkit listrik yang tidak dapat diprediksi. Pada penelitian kali ini akan disimulasikan PLTPH dengan tanpa control, control PID FA, control CES dan control PID CES FA. Dari keempat model simulasi PLTPH serta hubungan diagram responnya, maka dapat disimpulkan bahwa bahwa kontroler terbaik pada penelitian ini adalah PID-CES FA yaitu didapatkan undershoots sebesar -0.000002324 dan overshoot 0.0000004965 dengan settling time 3,026 detik. Dengan diterapkan metode PID-CES FA terhadap PLTPH, maka akan dapat menghasilkan frekuensi yang lebih baik dibanding dengan menngunakan tanpa control, kontrol PID-FA maupun dengan kontrol CES saja
Perencanaan Pencahayaan Lampu Jalan Dengan Simulasi Dialux Untuk Efisiensi Energi Lutfi Cahyanto, Iqbal; Ali, Machrus; Nurohmah, Hidayatul
Jurnal FORTECH Vol. 6 No. 1 (2025): Jurnal FORTECH
Publisher : FORTEI (Forum Pendidikan Tinggi Teknik Elektro Indonesia)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56795/fortech.v6i1.6102

Abstract

Good street lighting planning is essential, especially in areas prone to accidents and crime. Good street lighting can reduce the risk of accidents and increase the sense of security in public areas, providing security, convenience, and comfort for road users, especially at night or in bad weather conditions. However, street lighting is often a significant source of energy consumption. Therefore, optimising the street lighting system to improve energy efficiency is necessary. The study results showed that the existing lighting system using 250 W high-pressure sodium (HPS) lamps has weaknesses in terms of energy efficiency and light distribution quality. Simulations using Dialux showed that the average luminance of existing lighting only reached 0.6 cd/m² with a uniformity level of 0.4, and energy consumption reached 20,000 W along the road. Lighting optimization using 120 W LED lamps provides significant improvements in energy efficiency and lighting quality. The average luminance increased to 0.8 cd/m² with a uniformity of 0.6, while energy consumption decreased by 52%, from 20,000 W to 9,600 W. In addition, the glare level decreased from 30 to 25, indicating an increase in visual comfort. These results indicate that the implementation of LED lights can not only improve the quality of street lighting but also have a positive impact on energy efficiency and reduced operating costs.
Desain Optimasi PID Controller Pada Temperatur Heating Furnace Berbasis Ant Colony Algorithm (ACO) Kusuma Apsari, Venda; Ali, Machrus; Nurohmah, Hidayatul; Rukslin, Rukslin
Jurnal FORTECH Vol. 2 No. 2 (2021): Jurnal FORTECH
Publisher : FORTEI (Forum Pendidikan Tinggi Teknik Elektro Indonesia)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56795/fortech.v2i2.204

Abstract

A furnace is a tool for heating materials, oil, and so on, which usually uses gas, coal, and oil as fuel. Temperature is the main parameter that needs to be controlled in order to remain stable, precise, and of course improve fuel efficiency. As technology develops, there are several methods that can be used to control temperatures that are more reliable than conventional controls. The technology is Proportional Integral Derivative (PID) controller. PID controllers have been proven to be the best controllers and are widely used in industry. But to determine the gain from the PID value is still not accurate and can affect temperature stability, the response is also still slow to reach the desired set point. Therefore, this paper is to simulate a better PID gain value by using the artificial intelligence tuning method. The artificial intelligence method is Ant Colony Optimization (ACO). The simulation results and discussion show that the best design is PID-ACO with 0.0081 overshot, no undershot, and the fastest settling time is 35 seconds
Optimasi Kontrol Suhu Tungku Pemanas Menggunakan Metode Firefly Algorithm (FA) Rizal Anas, Febrian; Ajiatmo, Dwi; Nurohmah, Hidayatul; Ali, Machrus
Jurnal FORTECH Vol. 4 No. 2 (2023): Jurnal FORTECH
Publisher : FORTEI (Forum Pendidikan Tinggi Teknik Elektro Indonesia)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56795/fortech.v4i2.4203

Abstract

A furnace is a piece of equipment used to heat or change shape. Process control is becoming increasingly important in industry, as a consequence of global competition. Year after year, furnaces have progressed in both industrial processes and equipment. The tuning process ensures that system performance meets operating objectives. Intelligent control based on Artificial Intelligent (AI) has developed a lot to improve conventional control to control voltage loads and is always under constant variable assessment. The research results show that the best optimization method is produced by the PID-FA method which produces overshoot = 0.0721, undershoot 0.0081, and settling time at 30.4283 seconds. The PID-FA method produces better performance, according to the desired settings, so that fuel use can have a high level of efficiency
Optimasi Pembangkitan Ekonomis Berbasis Whale Optimization Algorithm Pada Sistem Multimesin Nurohmah, Hidayatul; Sula Cakra Buana, Arya; Rukslin, Rukslin; Ruswandi Djalal, Muhammad
Jurnal FORTECH Vol. 6 No. 2 (2025): In Progress
Publisher : FORTEI (Forum Pendidikan Tinggi Teknik Elektro Indonesia)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56795/fortech.v6i2.6102

Abstract

This study addresses the problem of generation cost optimization for thermal power plants in the Sulbagsel multimachine power system. An advanced swarm intelligence approach, the Whale Optimization Algorithm (WOA), is employed as the primary optimization technique. WOA, inspired by the bubble-net hunting strategy of humpback whales, has emerged as a promising metaheuristic with strong capabilities in exploration and exploitation. The main objective of this study is to minimize thermal generation costs while ensuring effective performance under real system operating conditions. To provide a comparative benchmark, Particle Swarm Optimization (PSO) is also applied to the same problem. Statistical evaluation is conducted to assess convergence behavior, accuracy, and consistency of both methods. The results indicate that WOA demonstrates superior balance between exploration and exploitation, leading to stable convergence and reliable solutions. Under peak daytime load conditions, PSO achieves a cost reduction of 23.02%, whereas the proposed WOA-based method achieves a comparable reduction of 23.78%. Although PSO yields a slightly higher cost saving, WOA demonstrates stronger robustness and statistical reliability across multiple trials. These findings confirm that WOA is a competitive alternative for generation cost optimization in complex multimachine systems, offering significant potential for future applications in economic dispatch problems with larger-scale renewable energy integration.