Atmaja, Sri Dewi and Satiawan, I Nyoman Wahyu and Supriono, Supriono and Citarsa, Ida Bagus Fery (2023) Pemodelan Buck-Boost Converter dengan Kendali Artificial Neural Network untuk Pengisian Baterai pada Sistem Photovoltaic. Dielektrika, 10 (1). pp. 64-71. ISSN 2086-9487
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Abstract
Indonesia has a huge potential for solar energy due to its territory is located on the equator. Solar energy is converted into electrical energy through solar panels or photovoltaic (PV). The electrical energy generated by PV can be directly used to supply loads or stored in a battery. This research investigates the design of a battery charging system controlled by Artificial Neural Networks (ANN). The battery charging system is modeled using Matlab/Simulink. ANN is trained using input and output data obtained from the system controlled by PI. ANN is trained with Back Propagation algorithm. The results show that the Buck-Boost Converter is able to maintain a relatively constant battery charging voltage, between 12.93 V - 14.01 V, at a PV output voltage between 14.01 V - 15.72 V. Meanwhile, the response performances generated by PI control and ANN are the same, the largest value of overshoot is 4.99% and the maximum settling time is 7.16 s. Response performance of the system controlled by PI and ANN tends to be the same. This is caused by the process training of ANN is not optimal because the limited training data used in this research.
| Item Type: | Article |
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| Keywords (Kata Kunci): | Photovoltaic; Buck-Boost Converter;PI (Proportional Integratif); Artificial Neural Network; Battery |
| Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering |
| Divisions: | Fakultas Teknik |
| Depositing User: | I Nyoman Wahyu Satiawan, S.T.M.Sc |
| Date Deposited: | 16 May 2023 02:40 |
| Last Modified: | 16 May 2023 02:40 |
| URI: | http://eprints.unram.ac.id/id/eprint/37967 |
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