Perancangan Discrete Single Axis Solar Tracker 5 Posisi Berbasis Kontrol Adaptive Neuro-fuzzy Inference System (ANFIS)

Apriliawardhani, Putri (2024) Perancangan Discrete Single Axis Solar Tracker 5 Posisi Berbasis Kontrol Adaptive Neuro-fuzzy Inference System (ANFIS). Other thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Salah satu aplikasi dalam pemanfaatan energi surya adalah photovoltaic (PV). Perubahan sudut kemiringan akibat perubahan posisi matahari sepanjang hari mengakibatkan penurunan daya output PV. Diperlukan Solar tracking system untuk memaksimalkan output dari PV tersebut. Solar tracker single axis adalah teknik untuk melacak matahari dari satu sisi ke sisi lain menggunakan titik poros tunggal untuk berputar yaitu horizontal, vertikal, dan miring. Pada penelitian dirancang photovoltaic dengan sistem discrete solar tracker single axis menggunakan metode kontrol Adaptive Neuro-Fuzzy Inference System (ANFIS) untuk mengurangi konsumsi internal energi dari solar tracker. Tujuan utama penelitian ini adalah mengetahui parameter perancangan dan performansi sistem discrete single axis solar tracker berbasis kontrol Adaptive Neuro-Fuzzy Inference System (ANFIS). Diperoleh respon kontrol sistem discrete single axis solar tracker untuk sumbu pitch dengan nilai Rise time: 0.15s, settling time: 5.85s, dan Ess: 0.14 %, sedangkan untuk sumbu yaw diperoleh nilai Rise time: 0.22s, settling time: 6.08s, dan Ess: 0.22 %. Performansi peningkatan energi bersih Discrete single axis Solar Tracker sumbu Pitch 3 posisi dan 5 posisi masing-masing sebesar 19.74%, dan 15.57% terhadap PV fixed. Sedangkan Discrete single axis Solar Tracker sumbu Yaw 3 posisi dan 5 posisi masing-masing sebesar 27.34%, dan 25.40% terhadap PV fixed. Saat diaplikasikan pada prototype, didapatkan performansi peningkatan energi bersih Discrete single axis Solar Tracker sumbu Pitch 3 posisi dan 5 posisi masing-masing sebesar 20.42%, dan 18.98% terhadap PV fixed. Sedangkan Discrete single axis Solar Tracker sumbu Yaw 3 posisi dan 5 posisi masing-masing sebesar 28.79%, dan 28.23% terhadap PV fixed.
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One application of solar energy utilization is photovoltaic (PV) systems. The changing tilt angle due to the sun's movement throughout the day results in a decrease in PV output power. A solar tracking system is required to maximize the output from the PV system. A single-axis solar tracker is a technique to track the sun from one side to the other using a single pivot point to rotate, either horizontally, vertically, or inclined. This study designs a photovoltaic system with a discrete single-axis solar tracker using the Adaptive Neuro-Fuzzy Inference System (ANFIS) control method to reduce the internal energy consumption of the solar tracker. The main objective of this research is to determine the design parameters and performance of a discrete single-axis solar tracker system based on ANFIS control. The control response of the discrete single-axis solar tracker for the pitch axis yielded a rise time of 0.15s, a settling time of 5.85s, and a steady-state error (Ess) of 0.14%, while for the yaw axis, the rise time was 0.22s, the settling time was 6.08s, and the Ess was 0.22%. The performance improvement in net energy for the discrete single-axis solar tracker with 3 position and 5 position pitch axes was 19.74%, and 15.57%, respectively, compared to a fixed PV. For the yaw axis, the discrete single axis solar tracker with 3 position and 5 position showed an improvement of 27.34%, dan 25.40%, respectively, compared to a fixed PV. When applied to a prototype, the performance improvement in net energy for the discrete single axis solar tracker with 3 position and 5 position pitch axes was 20.42%, dan 18.98%, respectively, compared to a fixed PV. For the yaw axis, the discrete single axis solar tracker with 3 position and 5 position showed an improvement of 28.79%, dan 28.23%, respectively, compared to a fixed PV.

Item Type:	Thesis (Other)
Uncontrolled Keywords:	Adaptive Neuro-Fuzzy Inference System Controller, Discrete Single Axis Solar Tracker, Solar Tracker, Adaptive Neuro-Fuzzy Inference System Controller, Discrete Passive Solar Tracker, Solar Tracker
Subjects:	Q Science > QC Physics > QC100.5 Measuring instruments (General) Q Science > QC Physics > QC271.8.C3 Calibration T Technology > T Technology (General) > T57.62 Simulation T Technology > T Technology (General) > T58.8 Productivity. Efficiency T Technology > TJ Mechanical engineering and machinery > TJ810.5 Solar energy
Divisions:	Faculty of Industrial Technology > Physics Engineering > 30201-(S1) Undergraduate Thesis
Depositing User:	Putri Apriliawardhani
Date Deposited:	05 Aug 2024 02:48
Last Modified:	05 Aug 2024 02:48
URI:	http://repository.its.ac.id/id/eprint/109736

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