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Ant Colony Optimazation sebagai Tuning PID pada Single Axis Tracking Photovoltaic Wahyu Cahyono; Mahrus Ali; Hidayatul Nurohmah; Budiman
SinarFe7 Vol. 2 No. 1 (2019): Sinarfe7-2 2019
Publisher : FORTEI Regional VII Jawa Timur

Show Abstract | Download Original | Original Source | Check in Google Scholar

Ant Colony Optimization (ACO) adalah Kecerdasan Buatan sering digunakan agar diperoleh optimasi suatu sistem. Ant Colony Optimization, berasal dari kata ant: semut, colony: kompulan atau koloni, opimization: optimasi semut merupakan tergolong salah satu hewan yang pintar, mereka mampu mencapai makannanya dengan jalur yang terpendek dan tercepat. Perilaku semut adalah inspirasi untuk Algoritma Ant Colony Optimization ini. Salah satu penggunaan metide ini adalah untuk meningkatkan efisiensi kontrol pergerakan panel surya yaitu dengan menambahkan sistem kendali single axis tracking matahari. Sistem kendali tracking matahari adalah sistem kendali yang selalu mengikuti posisi matahari. Tujuan dari sistem tracking matahari ini adalah untuk menempatkan penampang agar selalu dalam posisi menghadap ke arah posisi sinar matahari. Tracking matahari jenis azimuth- elevation terdiri dari sumbu putar horisontal dan sumbu putar vertikal. Sistem kontrol perlu sekali untuk dioptimasi agar posisi tepat sesuai yang diinginkan. Penelitian ini nanti bisa dipakai sebagai acuan dan digunakan kontroler lain atau metode kecerdasan buatan lainnya agar diperoleh kontroler yang optimal.

Desain Baterai Lithium-Ion Pengaruh Iradian Dan Temperatur Menggunakan PV Syst and Meteonorm Software Izzatul Umami; Intan Sekar Novitasari; Hidayatul Nurohmah; Dwi Ajatmo; Ali, Machrus
Elconika: Jurnal Teknik Elektro Vol. 2 No. 2 (2024)
Publisher : Universitas Hasyim Asy`ari

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33752/elconika.v2i2.7680

Indonesia is a country with significant potential for developing solar energy. However, one of the challenges in the electricity sector is the reliance on fossil fuels as the primary energy source. To mitigate the impact of this dependence on fossil fuels, it is crucial to explore new sources of renewable electricity. Solar cells, which convert sunlight or ultraviolet (UV) rays into electrical current, offer a promising solution. Sunlight is a sustainable and abundant energy source, making it a viable option for future energy production. Due to the nature of solar cells, which depend on sunlight, the output they produce is variable and influenced by changing weather conditions. Therefore, energy storage solutions, such as lithium-ion batteries, are needed to store the electricity generated by solar cells. This study will examine the characteristics and efficiency of solar cell input on the capacity of lithium-ion battery storage systems, focusing on the relationship between sunlight intensity and the generated current and voltage. An off-grid photovoltaic (PV) system relies solely on solar energy, utilizing a series of photovoltaic modules. Consequently, sunlight intensity significantly impacts the solar cell's performance by affecting the voltage and current produced, which in turn influences the system's performance. This research aims to assess the efficiency, advantages, and disadvantages of comparing the output results between series and parallel configurations of solar cells to meet desired needs. Testing and data collection will be conducted using simulations with PV Syst and Meteonorm software.

Desain Baterai Lithium-Ion Pengaruh Iradian Dan Temperatur Menggunakan PV Syst and Meteonorm Software Izzatul Umami; Intan Sekar Novitasari; Hidayatul Nurohmah; Dwi Ajatmo; Ali, Machrus
Elconika: Jurnal Teknik Elektro Vol. 2 No. 2 (2024)
Publisher : Universitas Hasyim Asy`ari

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33752/elconika.v2i2.7680

Indonesia is a country with significant potential for developing solar energy. However, one of the challenges in the electricity sector is the reliance on fossil fuels as the primary energy source. To mitigate the impact of this dependence on fossil fuels, it is crucial to explore new sources of renewable electricity. Solar cells, which convert sunlight or ultraviolet (UV) rays into electrical current, offer a promising solution. Sunlight is a sustainable and abundant energy source, making it a viable option for future energy production. Due to the nature of solar cells, which depend on sunlight, the output they produce is variable and influenced by changing weather conditions. Therefore, energy storage solutions, such as lithium-ion batteries, are needed to store the electricity generated by solar cells. This study will examine the characteristics and efficiency of solar cell input on the capacity of lithium-ion battery storage systems, focusing on the relationship between sunlight intensity and the generated current and voltage. An off-grid photovoltaic (PV) system relies solely on solar energy, utilizing a series of photovoltaic modules. Consequently, sunlight intensity significantly impacts the solar cell's performance by affecting the voltage and current produced, which in turn influences the system's performance. This research aims to assess the efficiency, advantages, and disadvantages of comparing the output results between series and parallel configurations of solar cells to meet desired needs. Testing and data collection will be conducted using simulations with PV Syst and Meteonorm software.

AI-Assisted PID Tuning for Voltage Control of an Axial-Flow Pico-Hydro Generator Ali, Machrus; Hidayatul Nurohmah; Muhammah Agil Haikal; Yanuar Mahfudz Safarudin
Journal of Renewable Energy and Smart Device Vol. 3 No. 2 April 2026
Publisher : PT. Global Research Collaboration

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66314/joresd.v3i2.691

Pico hydropower is a renewable-energy option for isolated communities and low-head run-of-river sites, but axial-flow pico-hydro generators are vulnerable to voltage fluctuation when water flow, hydraulic head, or consumer load changes. This study proposes a novel and reproducible artificial-intelligence-assisted proportional-integral-derivative (PID) tuning framework for voltage control of a 220 V, 2 kW axial-flow turbine generator ZD760-LM-(18-20). The novelty lies in combining a voltage-control-oriented small-signal model of a low-head axial-flow pico-hydro unit, a nonminimum-phase hydraulic zero that represents inverse initial response, identical bounded PID-search constraints, and a composite objective that explicitly penalizes inverse dip, overshoot, settling time, ITAE, and IAE. The plant model combines actuator or electronic-load-controller dynamics, non-elastic water-column dynamics, turbine-generator dynamics, and sensor dynamics. PID gains obtained from Ziegler-Nichols (PID-ZN), Ant Colony Optimization (PID-ACO), and Particle Swarm Optimization (PID-PSO) are compared under Kp = 0-100, Ki = 0-50, and Kd = 0-10. Simulation results show that PID-ZN stabilizes the plant but requires a 6.80 s settling time and produces an ITAE of 2.9603. PID-ACO reduces settling time to 2.26 s and ITAE to 1.1320, whereas PID-PSO gives the lowest ITAE of 1.1311 with only 0.030% overshoot. Compared with PID-ZN, PID-PSO reduces settling time by 66.8% and ITAE by 61.8%. These results indicate that AI-based PID tuning can improve voltage quality in low-cost rural and off-grid pico-hydro systems using practical ELC or simple actuator implementations.

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