Optimal Sizing of Hybrid - Battery - Supercapacitor - Generator Storage System in Electric Ship using Genetic Algorithm

Sorn, Chanraksa (2025) Optimal Sizing of Hybrid - Battery - Supercapacitor - Generator Storage System in Electric Ship using Genetic Algorithm. Masters thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Emisi bahan bakar fosil dari kapal berdampak signifikan pada perubahan iklim, kualitas lingkungan, dan kesehatan manusia. Sektor kelautan pun semakin tertarik untuk menerapkan solusi energi yang lebih ramah lingkungan dan berkelanjutan. Kapal propulsi listrik yang ditenagai oleh penyimpanan energi hibrida memiliki kemampuan untuk menurunkan emisi, meningkatkan kualitas daya, dan menurunkan konsumsi bahan bakar. Ada banyak jenis system penyimpanan energi seperti baterai, superkapasitor, hidrogen, dll. Dalam penelitian ini, gabungan baterai dan superkapasitor dipilih sebagai sistem penyimpanan energi hibrida untuk memasok daya ke kapal listrik dan generator diesel sebagai sumber daya tambahan. Tujuan utamanya adalah untuk menentukan ukuran sistem penyimpanan energi hibrida guna meminimalkan total biaya sambilmempertahankan pasokan energi yang andal. Ukuran optimal setiap komponen dilakukan di MATLAB menggunakan Algoritma Genetika.
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The fossil fuel emissions from the ship have significant impacts on climate change, environmental quality, and human health. The marine sector has consequently grown increasingly interested in implementing greener and more sustainable energy solutions. The electric propulsion ship is powered by hybrid energy storage has the ability to lower emissions, improve the power quality, and lower fuel consumption. There are many types of energy storage system such as battery, supercapacitor, hydrogen, etc. In this study, the combine of battery and supercapacitor are chosen as a hybrid energy storage system to supply power to the electric ship and diesel generator is an additional power source. The main objective is to sizing the hybrid energy storage system to minimize the total cost while maintaining reliable energy supply. The optimal sizing of each component is conducted in MATLAB using Genetic Algorithm.

Item Type:	Thesis (Masters)
Uncontrolled Keywords:	Hybrid Energy Storage System (HESS), Battery, Supercapacitor (SC), Diesel Generator (DG), Genetic Algorithm (GA)
Subjects:	T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK2941 Storage batteries T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7872.C65 Supercapacitors.
Divisions:	Faculty of Intelligent Electrical and Informatics Technology (ELECTICS) > Electrical Engineering > 20101-(S2) Master Thesis
Depositing User:	Chanraksa Sorn
Date Deposited:	21 Jul 2025 02:50
Last Modified:	21 Jul 2025 02:50
URI:	http://repository.its.ac.id/id/eprint/120174

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