Perancangan MPPT Dengan Metode Grey Wolf Optimization Pada Sistem Panel Surya Fotovoltaik

Rusdy, Raziq Altaf (2025) Perancangan MPPT Dengan Metode Grey Wolf Optimization Pada Sistem Panel Surya Fotovoltaik. Other thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Penelitian ini membahas perancangan algoritma Maximum Power Point Tracking (MPPT) berbasis metode Grey Wolf Optimization (GWO) untuk meningkatkan efisiensi daya keluaran sistem panel surya fotovoltaik. Algoritma GWO dirancang untuk mengatasi kelemahan MPPT konvensional, seperti Perturb and Observe (P&O), yang kurang stabil dan efektif dalam menghadapi kondisi lingkungan yang berubah-ubah, seperti intensitas cahaya tidak merata dan bayangan parsial. Metode GWO memanfaatkan pola perilaku serigala abu-abu dalam berburu mangsa untuk mencari titik daya maksimum (Maximum Power Point) secara adaptif dan dinamis. Hasil simulasi menunjukkan bahwa algoritma P&O memiliki waktu pelacakan yang lebih cepat dan efisiensi rata-rata yang lebih tinggi, yaitu sebesar 89,9%, dibandingkan dengan GWO yang mencatat efisiensi rata-rata 85,7% dalam durasi simulasi terbatas. Meskipun demikian, algoritma GWO menunjukkan potensi dalam pencarian titik daya maksimum secara global, namun memerlukan waktu konvergensi yang lebih panjang untuk mencapai kestabilan daya.
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This study discusses the design of a Maximum Power Point Tracking (MPPT) algorithm based on the Grey Wolf Optimization (GWO) method to improve the power output efficiency of photovoltaic solar panel systems. The GWO algorithm is designed to address the limitations of conventional MPPT methods, such as Perturb and Observe (P&O), which are less stable and effective in dealing with varying environmental conditions, such as uneven light intensity and partial shading. The GWO method leverages the behavioral patterns of grey wolves in hunting prey to adaptively and dynamically search for the maximum power point (MPP). Simulation results show that the P&O algorithm has faster tracking time and higher average efficiency, at 89.9%, compared to GWO, which recorded an average efficiency of 85.7% over a limited simulation duration. However, the GWO algorithm demonstrates potential in global maximum power point search but requires a longer convergence time to achieve power stability.

Item Type:	Thesis (Other)
Uncontrolled Keywords:	MPPT, Grey Wolf Optimization, Panel Surya, Buck Converter.
Subjects:	T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK1056 Solar power plants. Ocean thermal power plants
Divisions:	Faculty of Vocational > 36304-Automation Electronic Engineering
Depositing User:	Raziq Altaf Rusdy
Date Deposited:	15 Aug 2025 03:19
Last Modified:	15 Aug 2025 03:19
URI:	http://repository.its.ac.id/id/eprint/128117

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