Manararrahmat, Rizqi Lazuardy (2020) Analisis Performansi Sistem Charging Output Ganda Terintegrasi Pada Solar Energy Berbasis Algoritma Ant Colony Optimization - Fuzzy Logic. Other thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Sistem yang dirancang adalah sistem charging baterai output ganda terintegrasi dengan sistem solar energi menggunakan konverter Buck single input dual output untuk menyuplai daya pada baterai 12 V dan baterai 24 V. Photovoltaic Standalone off-grid yang digunakan sebagai sumber energi tunggal menghasilkan energi yang dapat dimanfaatkan dan butuh untuk disimpan kedalam baterai. output tegangan PV yang perlu untuk dikondisikan agar dapat mengisi baterai merupakan tantangan yang akan dihadapi dalam pengendalian pada sistem charging baterai. sehingga dibutuhkan teknologi yang cerdas untuk menghadapi masalah tersebut. solusi yang ditawarkan berupa pengendalian fuzzy logic yang telah dioptimisasi menggunakan algoritma Ant Colony Optimization (ACO-FLC). Adapun pengendalian ACO-FLC menunjukkan hasil performansi settling time, maximum overshoot, ripple tegangan, dan error steady state masing-masing bernilai 0,012 detik ; 15,7% ; 0,16 V ; 0,6% untuk charging baterai 24 V dan pada charging baterai 12 V bernilai 0,017 detik ; 36,3% ; 0,17 V ; 0,4%. Hasil optimisasi dapat menurunkan settling time, ripple tegangan, maximum overshoot dan error steady state, sehingga dapat disimpulkan pengendalian ACO-FLC meningkatkan performansi pada output tegangan yang dibutuhkan baterai.
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The system designed is a dual output battery charging system integrated with a solar energy system using a single input dual output Buck converter to supply power to 12 V battery and 24 V battery. Off-grid photovoltaic battery used as a single source of energy to produce energy that can be utilized and need to be stored in the battery. PV output voltage that needs to be conditioned in order to charge the battery is a challenge that will be faced in controlling the battery charging system. so it takes intelligent technology to deal with these problems. The solution offered is in the form of fuzzy logic control that has been optimized using the Ant Colony Optimization (ACO-FLC) algorithm. c. The ACO-FLC control shows the settling time performance results, maximum overshoot, voltage ripple, and steady state error, each worth 0.012 seconds; 15,7% ; 0,16 V ; 0,6% for charging a 24 V battery and charging a 12 V battery is 0.017 seconds; 36,3% ; 0,17 V ; 0,4%. Optimization results can reduce settling time, voltage ripple, maximum overshoot and steady state error, so it can be concluded that ACO-FLC control increases the performance of the voltage output required by the battery.
| Item Type: | Thesis (Other) |
|---|---|
| Uncontrolled Keywords: | Solar Energi, Photovoltaic, Baterai, Fuzzy Logic, Ant Colony, Solar Energy, Photovoltaic, Battery, Fuzzy Logic, Ant Colony |
| Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK201 Electric Power Transmission T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK1007 Electric power systems control T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK1056 Solar power plants. Ocean thermal power plants T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK1087 Photovoltaic power generation |
| Divisions: | Faculty of Industrial Technology and Systems Engineering (INDSYS) > Physics Engineering > 30201-(S1) Undergraduate Thesis |
| Depositing User: | Rizqi Lazuardy Manararrahmat |
| Date Deposited: | 12 Aug 2020 05:11 |
| Last Modified: | 29 May 2023 08:15 |
| URI: | http://repository.its.ac.id/id/eprint/77649 |
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