Optimasi Sistem Pengisian MPPT Berbasis Fuzzy logic Pada Panel Surya
Keywords:
Photovoltaic, MPPT, Fuzzy logic, Battery Charging, Renewable Energy, Power OptimizationAbstract
The transition to renewable energy is a crucial step in achieving sustainable development. However, the efficiency of Photovoltaic (PV) systems remains a challenge due to fluctuations in solar irradiation, which affect power generation. This study aimed to enhance Maximum Power Point Tracking (MPPT) performance by integrating Fuzzy logic Control (FLC) into the charging system of a solar power plant. The research employed an experimental approach involving the testing of a 100 Wp PV module and a 44 Ah battery, where data collection was conducted at 10-minute intervals from 10:30 AM to 3:00 PM. The proposed FLC-based MPPT system was compared with a conventional MPPT system to evaluate charging efficiency, power stability, and response time. The findings indicated that the FLC-based MPPT exhibited superior stability, maintaining output voltage within 12V to 12.5V, whereas the non-Fuzzy MPPT showed wider voltage variations. Additionally, the FLC-based system achieved an average charging current of 2.05 A, reducing the full battery charging time to 21 hours 46 minutes, compared to 46 hours 31 minutes for the conventional MPPT system. These results confirm that FLC enhances MPPT performance, particularly in optimizing power output and reducing charging time. However, efficiency trade-offs were observed due to step-down losses in the buck converter. Future research should focus on hybrid MPPT approaches, parameter optimization, and large-scale implementation, potentially integrating Artificial Intelligence (AI) techniques to further improve efficiency. This study contributes to advancing intelligent MPPT systems for renewable energy applications.
References
A. Khaffi, A. Rosyid Idris, J. Teknik Elektro, and P. Negeri Ujung Pandang, “Rancang Bangun Modul Trainer Pembangkit Listrik Tenaga Surya (PLTS),” jurnal.poliupg.ac.idA Khaffi, AR Idris, S SofyanSeminar Nas. Tek. Elektro dan Inform. (SNTEI), 2020•jurnal.poliupg.ac.id, 2020, Accessed: Feb. 22, 2025. [Online]. Available: http://jurnal.poliupg.ac.id/index.php/sntei/article/view/2184
A. Y. Salile, S. Nisworo, and S. Sumardi, “Analisis Fluktuasi Radiasi Matahari dan Implikasinya Terhadap Penempatan PLTS,” J. Profesi Ins. Indones., vol. 2, no. 6, pp. 354–358, Dec. 2024, doi: 10.14710/JPII.2024.24596.
M. Anggara and W. Saputra, “Analisis Kinerja Sel Surya Monocrystalline dan Polycrystalline di Kabupaten Sumbawa NTB,” J. FLYWHEEL, vol. 14, no. 1, pp. 7–12, Feb. 2023, doi: 10.36040/FLYWHEEL.V14I1.6521.
A. Faizal, “DESAIN MAXIMUM POWER POINT TRACKING (MPPT) PADA PANEL SURYA MENGGUNAKAN METODE SLIDING MODE CONTROL,” SITEKIN J. Sains, Teknol. dan Ind., vol. 14, no. 1, pp. 22–31, Dec. 2016, doi: 10.24014/SITEKIN.V14I1.2103.
A. Tetuko, D. Djuniadi, and E. Apriaskar, “Analisis Kenerja Maximum Power Point Tracker (MPPT) Pada Sistem Photovoltaic Standalone Berbasis Algoritme Perturb And Observe (P&O),” PROtek J. Ilm. Tek. Elektro, vol. 8, no. 2, p. 72, 2021, doi: 10.33387/protk.v8i2.2768.
M. Ula, A. Rahmadani, and P. Elektronika Negeri Surabaya, “Rancang Bangun Maximum Power Point Tracking pada Panel Surya dengan Metode Incremental Conductance Menggunakan Zeta Konverter,” Techné J. Ilm. Elektrotek., vol. 22, no. 1, pp. 1–20, Apr. 2023, doi: 10.31358/TECHNE.V22I1.334.
M. HABIBI, M. N. HABIBI, D. N. PRAKOSO, N. A. WINDARKO, and A. TJAHJONO, “Perbaikan MPPT Incremental Conductance menggunakan ANN pada Berbayang Sebagian dengan Hubungan Paralel,” ELKOMIKA J. Tek. Energi Elektr. Tek. Telekomun. Tek. Elektron., vol. 8, no. 3, p. 546, Aug. 2020, doi: 10.26760/elkomika.v8i3.546.
H. Rusiana Iskandar et al., “Algoritma Incremental Conductance dan Perturbation Observation Sebagai Kendali MPPT PLTS 1000Wp,” J. Tek. Media Pengemb. Ilmu dan Apl. Tek., vol. 19, no. 2, pp. 79–89, Dec. 2020, doi: 10.26874/JT.VOL19NO02.151.
I. C. W. Aji, U. T. Kartini, S. I. Haryudo, and M. Widyartono, “Rancang Bangun Sistem Pompa Air Tenaga Surya Skala Rumah Tangga Menggunakan Maximum Power Point Tracking (MPPT) dengan Metode Algoritma Perturb dan Observe untuk Memaksimalkan Daya,” J. Tek. ELEKTRO, vol. 10, no. 3, pp. 629–638, Jul. 2021, doi: 10.26740/JTE.V10N3.P629-638.
A. H. Sangaji and T. Rijanto, “Maximum Power Point Tracking (MPPT) Menggunakan Metode Artificial Neural Network untuk Panel Surya,” J. Tek. Elektro, vol. 07, pp. 85–92, 2018.
I. G. Ferryawan, A. Natsir, and I. M. A. Nratha, “MAXIMUM POWER POINT TRACKING (MPPT)PADA SISTEM FOTOVOLTAIK DENGAN BOOST CONVERTER BERBASIS LOGIKA FUZZY,” DIELEKTRIKA, vol. 4, no. 2, pp. 147–154, Oct. 2017, Accessed: Feb. 23, 2025. [Online]. Available: https://dielektrika.unram.ac.id/index.php/dielektrika/article/view/85
H. P. Waseso, A. Lomi, and A. U. Krismanto, “Sistem Kendali MPPT Berbasis Fuzzy Logic Pada Pembangkit Listrik Tenaga Surya,” Magn. J. Mhs. Tek. Elektro, vol. 8, no. 1, pp. 91–100, May 2024, Accessed: Feb. 23, 2025. [Online]. Available: https://ejournal.itn.ac.id/index.php/magnetika/article/view/10183
M. Z. Abdullah, I. Sudiharto, and R. P. Eviningsih, “Photovoltaic System MPPT using Fuzzy Logic Controller,” Proc. - 2020 Int. Semin. Appl. Technol. Inf. Commun. IT Challenges Sustain. Scalability, Secur. Age Digit. Disruption, iSemantic 2020, pp. 378–383, Sep. 2020, doi: 10.1109/ISEMANTIC50169.2020.9234200.
J. Lach, K. Wróbel, J. Wróbel, P. Podsadni, and A. Czerwiński, “Applications of carbon in lead-acid batteries: a review,” J. Solid State Electrochem., vol. 23, no. 3, pp. 693–705, Mar. 2019, doi: 10.1007/S10008-018-04174-5/FIGURES/9.
G. J. May, A. Davidson, and B. Monahov, “Lead batteries for utility energy storage: A review,” J. Energy Storage, vol. 15, pp. 145–157, Feb. 2018, doi: 10.1016/J.EST.2017.11.008.
N. M. Nasab and S. Yazdanian, “The advantages of lead-acid battery for off-grid design,” Energy Storage, vol. 6, no. 2, p. e595, Mar. 2024, doi: 10.1002/EST2.595.
M. Dabboussi, A. Hmidet, and O. Boubaker, “An efficient fuzzy logic MPPT control approach for solar PV system: A comparative analysis with the conventional perturb and observe technique,” 6th IEEE Int. Energy Conf. ENERGYCon 2020, pp. 366–371, Sep. 2020, doi: 10.1109/ENERGYCON48941.2020.9236503.
D. Remoaldo and I. S. Jesus, “Analysis of a Traditional and a Fuzzy Logic Enhanced Perturb and Observe Algorithm for the MPPT of a Photovoltaic System,” Algorithms 2021, Vol. 14, Page 24, vol. 14, no. 1, p. 24, Jan. 2021, doi: 10.3390/A14010024.
E. Kandemir, S. Borekci, and N. S. Cetin, “Comparative Analysis of Reduced-Rule Compressed Fuzzy Logic Control and Incremental Conductance MPPT Methods,” J. Electron. Mater., vol. 47, no. 8, pp. 4463–4474, Aug. 2018, doi: 10.1007/S11664-018-6273-Y/METRICS.
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