Amin, Richi Mohammad (2024) Strategi Alokasi Daya Pada Sistem Penyimpanan Energi Hibrida Dengan Menggunakan Metode Low Pass Filter (LPF). Other thesis, Institut Teknologi Sepuluh Nopember.
Text
5022201211-Undergraduate_Thesis.pdf - Accepted Version Restricted to Repository staff only until 1 October 2026. Download (8MB) | Request a copy |
Abstract
Sistem penyimpanan energi hibrida (Hybrid Energy Storage System/HESS) menjadi solusi potensial untuk mengatasi tantangan variabilitas dan ketidakkonstanan sumber energi terbarukan. Pengelolaan alokasi daya yang efektif dalam HESS menjadi krusial untuk memaksimalkan efisiensi dan keandalan sistem. Penelitian ini mengusulkan strategi alokasi daya menggunakan metode filter lolos rendah (LPF) untuk meningkatkan performa HESS. Metode LPF diterapkan untuk memisahkan komponen dengan frekuensi daya tinggi dan frekuensi daya rendah dalam aliran daya sistem. Komponen dengan frekuensi daya rendah dialokasikan ke baterai, sementara komponen dengan frekuensi daya tinggi dialokasikan ke superkapasitor. Hasil simulasi menunjukkan bahwa penggunaan karakteristik daya sumber dan variasi beban memiliki frekuensi cut-off optimal yang bervariasi. Pada karakteristik sumber PV, frekuensi cut-off optimal yang dimiliki adalah sebesar 0.00008 Hz. Sedangkan saat menggunakan sumber angin, frekuensi cut-off optimal yang dimiliki adalah sebesar 0.00016 Hz. Terakhir, untuk penerapan metode LPF pada kendaraan elektrik, memiliki frekuensi cut-off optimal sebesar 0.0159 Hz. Selain itu, penggunaan metode LPF berhasil menurunkan energi yang dimiliki oleh baterai secara signifikan pada masing-masing karakteristik. Pada karakteristik sumber PV, energi yang dimiliki oleh baterai menurun sebesar 3%-10%. Sedangkan pada sumber angin, menurun sebesar 1%-4%. Terakhir, untuk penerapan metode LPF pada kendaraan listrik, kebutuhan energi menurun sebesar 12%.
=====================================================================================================
Hybrid Energy Storage System (HESS) is a potential solution to overcome the challenges of variability and instability of renewable energy sources. Effective power allocation management in HESS is crucial to maximize system efficiency and reliability. This study proposes a power allocation strategy using the low-pass filter method (LPF) to improve HESS performance. The LPF method is applied to separate components with high power frequency and low power frequency in the system power flow. Components with low power frequencies are allocated to batteries, while components with high power frequencies are allocated to supercapacitors. The simulation results show that the use of source power characteristics and load variations have varying optimal cut-off frequencies. In the characteristics of the PV source, the optimal cut-off frequency is 0.00008 Hz. Meanwhile, when using a wind source, the optimal cut-off frequency is 0.00016 Hz. Finally, for the application of the LPF method in electric vehicles, it has an optimal cut-off frequency of 0.0159 Hz. In addition, the use of the LPF method has succeeded in significantly reducing the energy owned by the battery in each characteristic. In the characteristics of PV sources, the energy owned by batteries decreases by 3%-10%. Meanwhile, in wind sources, it decreased by 1%-4%. Finally, for the application of the LPF method in electric vehicles, energy demand decreased by 12%.
Item Type: | Thesis (Other) |
---|---|
Uncontrolled Keywords: | Sistem Penyimpanan Energi Hibrida (HESS), Filter Lolos Rendah (LPF), Alokasi Daya, Baterai, Superkapasitor. Hybrid Energy Storage System (HESS), Low Pass Filter (LPF), Power Allocation, Battery, Supercapacitor. |
Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK2941 Storage batteries |
Divisions: | Faculty of Intelligent Electrical and Informatics Technology (ELECTICS) > Electrical Engineering > 20201-(S1) Undergraduate Thesis |
Depositing User: | Amin Richi Mohammad |
Date Deposited: | 31 Jul 2024 06:44 |
Last Modified: | 31 Jul 2024 06:44 |
URI: | http://repository.its.ac.id/id/eprint/111195 |
Actions (login required)
View Item |