Devi, Laila Nurfitria (2024) Perancangan Continuous Dual Axis Solar Tracker Berbasis Kontrol Adaptive Neuro-Fuzzy Inference System (ANFIS). Other thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Salah satu cara untuk mengoptimalkan daya keluaran yang dihasilkan panel surya adalah menambah sistem solar tracker pada panel surya. Solar tracker merupakan sistem yang berfungsi sebagai penggerak panel surya untuk mengikuti arah pergerakan matahari agar selalu tegak lurus terhadap matahari. Sistem solar tracker aktif dua sumbu terdiri dari sensor LDR, kontroler, motor DC, panel surya, dan baterai. Panel surya bergerak pada dua sudut yaitu yaw dan pitch. Penelitian ini menggunakan kontroler Adaptive Neuro-Fuzzy Inference System (ANFIS). Hasil evaluasi perancangan sistem kontrol ANFIS mempunyai error MSE, RMSE, dan MAE berturut-turut adalah 0.0018, 0.0430, dan 0.0390 untuk sumbu pitch serta 0.0064, 0.0798, dan 0.0582 untuk sumbu yaw. Indeks performansi kontrol ANFIS yang telah dirancang pada continuous active solar tracker untuk simulasi dan eksperimen berturut-turut sebagai berikut nilai settling time sebesar 3.84 detik dan 4.04 detik, maximum overshoot sebesar 0.03% dan 0.17%, serta error steady state sebesar 0.13% dan 0.15%. Sedangkan performansi peningkatan energi secara netto baik secara simulasi maupun eksperimen masing-masing sebesar 41.2% dan 34.5%. Energi bersih yang diterima sistem dapat menambah persentase baterai pada simulasi dan eksperimen berturut-turut adalah 50.9% dan 50.2% untuk sistem solar tracker serta 37.8% dan 35.6% untuk sistem PV fixed. Perbedaan ini dapat disebabkan oleh berbagai faktor seperti kondisi lingkungan serta keterbatasan simulasi dalam mereplikasi kondisi eksternal yang dihadapi oleh hardware di lapangan.
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One way to optimize the output power produced by solar panels is to add a solar tracker system to the solar panels. A solar tracker is a system that functions as a solar panel driver to follow the direction of the sun's movement so that it is always perpendicular to the sun. The two-axis active solar tracker system consists of an LDR sensor, controller, DC motor, solar panel, and battery. The solar panel moves at two angles, namely yaw and pitch. This study uses the Adaptive Neuro-Fuzzy Inference System (ANFIS) controller. The results of the evaluation of the ANFIS control system design have MSE, RMSE, and MAE errors, respectively, of 0.0018, 0.0430, and 0.0390 for the pitch axis and 0.0064, 0.0798, and 0.0582 for the yaw axis. The performance of ANFIS control on continuous active solar tracker has performance index for simulation and experiment respectively as follows: settling time value of 3.84 seconds and 4.04 seconds, maximum overshoot of 0.03% and 0.17%, and steady state error of 0.13% and 0.15%. While the net energy increase performance both in simulation and experiment is 41.2% and 34.5% respectively. The net energy received by the system can increase the battery percentage in simulation and experiment respectively is 50.9% and 50.2% for solar tracker system and 37.8% and 35.6% for fixed PV system. This difference can be caused by various factors such as environmental conditions and simulation limitations in replicating external conditions faced by hardware in the field.
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