ajiatmo, dwi (2021) Desain dan Implementasi Optimisasi Kontrol Maximum Power Point Tracking (MPPT) Base On Hybrid Fuzzy Logic Controller - Firefly Algorithm (FLC-FA) Pada Sistem Photovoltaik (PV) Mobil Listrik. Doctoral thesis, Institut Teknolog Sepuluh Nopember.
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Abstract
Pada penelitian ini telah dilakukan metode MPPT berbasis fuzzy logic controller – firefly algorithm (FLC-FA) dalam meningkatkan kinerja photovoltaik untuk charging baterai sebagai sumber bagi mobil listrik. MPPT berbasis FLC-FA optimisasi yang digunakan adalah Firefly Algorithm dalam menenetukan membership function dari fuzzy logic controller, suatu metode yang memberikan suatu inovasi terhadap fungsi posisi dari kunang-kunang dalam mencari titik cahaya yang cerah. Firefly algorithm mempunyai suatu keunggulan dalam kecepatan dan konvergensi yang lebih baik guna menemukan titik yang optimal. Pada sistem kontrol MPPT fungsi keanggotaan/membership function fuzzy logic controller (FLC) selama ini dicari dengan cara menggunakan trial dan error, sehingga proses pencarian membership function ini banyak memakan waktu yang lama. Oleh karena itu proses pencarian membership function FLC dengan menggunakan Firefly Algorithm, sehingga diharapakan pencarian membership function akan lebih cepat dengan ketelitian yang lebih baik. Pengujian dilakukan menggunakan software PSIM dan Software Matlab dalam mensimulasikan komponen PV, DC-DC boost konverter, dan baterai. Pengujian dilakukan baik secara parsial maupun secara keseluruhan. Pengujian ini perlu dilakukan untuk mendapatkan hasil data riil dari kemampuan peralatan sebelum diaplikasikan kedalam prototipe mobil listrik.
Signifikansi hasil pengujian pada kondisi variasi intensitas cahaya dan variasi temperatur pada beban resistor akurasi kinerja tanpa MPPT adalah 69.45889% dan akurasi kinerja menggunakan MPPT berbasis FLC-FA adalah 98.852%. Pada pengujian beban baterai menunjukan akurasi kinerja tanpa MPPT adalah 96,69% dan akurasi kinerja menggunakan MPPT berbasis FLC adalah 99,99%. Sedangkan sistem prototipe boost converter memiliki efisiensi yang tinggi sebesar 91.1% dan nilai akurasi di 97.5591%.
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In this study, the MPPT method based on fuzzy logic controller - firefly algorithm (FLC-FA) has been carried out to improve the performance of photovoltaic for charging batteries as a source for electric cars. The MPPT based on FLC-FA optimization used is the Firefly Algorithm in determining the membership function of the fuzzy logic controller, a method that provides an innovation in the position function of fireflies in finding bright points of light. Firefly algorithm has an advantage in speed and better convergence to find the optimal point. In the MPPT control system, the membership function fuzzy logic controller (FLC) has been searched for by trial and error, so the membership function search process takes a long time. Therefore, the search process for the membership function of FLC uses the Firefly Algorithm, so it is expected that the search for membership function will be faster with better accuracy. Tests were carried out using PSIM software and Matlab software in simulating the PV components, DC-DC boost converter, and batteries. Testing is carried out either partially or as a whole. This test needs to be done to get real data results from the capabilities of the equipment before it is applied to an electric car prototype.
The significance of the test results on the conditions of variations in light intensity and temperature variations on the load resistor, the performance accuracy without MPPT is 69.45889% and the performance accuracy using MPPT based on FLC-FA is 98.852%. In the battery load test, the performance accuracy without MPPT is 96.69% and the performance accuracy using FLC-based MPPT is 99.99%. While the boost converter prototype system has high efficiency of 91.1% and an accuracy value of 97.5591%.
| Item Type: | Thesis (Doctoral) |
|---|---|
| Uncontrolled Keywords: | MPPT, Fuzzy Logic Control, Firefly Algorithm, Photovoltaik MPPT, Fuzzy Logic Control, Firefly Algorithm, Photovoltaic |
| Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering |
| Divisions: | Faculty of Intelligent Electrical and Informatics Technology (ELECTICS) > Electrical Engineering > 20001-(S3) PhD Thesis |
| Depositing User: | Dwi Ajiatmo |
| Date Deposited: | 03 Mar 2021 03:23 |
| Last Modified: | 03 Mar 2021 03:24 |
| URI: | http://repository.its.ac.id/id/eprint/83240 |
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