Rekonfigurasi Dinamis Jaring Distribusi Menggunakan Binary Particle Swarm Optimization untuk Meningkatkan Voltage Stability Index

Hakim, Mochammad Naufal (2024) Rekonfigurasi Dinamis Jaring Distribusi Menggunakan Binary Particle Swarm Optimization untuk Meningkatkan Voltage Stability Index. Other thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Saat ini, permintaan daya listrik pada sistem distribusi telah meningkat secara signifikan, sehingga meningkatkan rugi-rugi daya pada sistem. Distributed Generation (DG) berbasis energi terbarukan digunakan untuk membantu memenuhi permintaan daya tersebut. Namun, hal ini memiliki efek samping yaitu menimbulkan ketidakpastian pada sistem karena sifat intermiten dari sumber energi terbarukan. Oleh sebab itu, tugas akhir ini disusun untuk mengatasi permasalahan rugi-rugi daya dan kestabilan tegangan dengan rekonfigurasi dinamis jaringan distribusi menggunakan algoritma Binary Particle Swarm Optimization (BPSO). Rekonfigurasi dinamis dilakukan dengan membagi rentang waktu 24 jam menjadi tiga interval. Sistem jaring distribusi dimodifikasi dari sistem IEEE 69-bus terintegrasi dengan DG yang terdiri dari sistem photovoltaic (PV). Beban residensial, industrial, dan komersial dimodelkan pada sistem distribusi untuk mendapatkan profil beban selama 24 jam. Stability Index (SI)dan rugi-rugi daya diformulasikan sebagai fungsi objektif algoritma BPSO. Hasil optimasi menghasilkan topologi sistem baru untuk setiap interval. Hasil rekonfigurasi dinamis tiga interval dengan penambahan DG pada sistem menunjukkan bahwa rugi-rugi daya aktif dan reaktif mengalami penurunan sebesar 77,606% dan 39,538% secara berurutan. Di samping itu, nilai SI minimum dan tegangan minimum sistem mengalami peningkatan sebesar 96,934% dan 18,487% secara berurutan. Rekonfigurasi dinamis menggunakan algoritma BPSO terbukti dapat mengurangi rugi-rugi daya dan meningkatkan kestabilan tegangan pada sistem distribusi yang terintegrasi dengan DG.
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Currently, the demand for electrical power in the distribution system has significantly increased, thereby increasing power losses in the system. Distributed Generation (DG) based on renewable energy sources is utilized to fulfill the power demand. However, this has the side effect of introducing uncertainty into the system due to the intermittent nature of renewable energy sources. Therefore, this thesis aims to address the issues of power losses and voltage stability by utilizing dynamic reconfiguration of the distribution network using Binary Particle Swarm Optimization (BPSO). Dynamic reconfiguration was performed by dividing the 24-hour cycle into three intervals. The distribution network was modified from the IEEE 69-bus system integrated with DG consisting of photovoltaic (PV) systems. Residential, industrial, and commercial load profiles were modeled on the distribution system to obtain a 24-hour load profile. Stability Index (SI) and power losses were formulated as the objective functions of the BPSO algorithm. The optimization results produced a new system topology for each interval. The result of three-interval dynamic reconfiguration showed that active and reactive power losses were reduced by 77,606% and 39,538%, respectively. Additionally, the minimum SI value and the minimum system voltage were increased by 96,934% and 18,487%, respectively. Dynamic reconfiguration using the BPSO algorithm has proven to reduce power losses and improve voltage stability in the distribution system integrated with DG.

Item Type:	Thesis (Other)
Uncontrolled Keywords:	binary particle swarm optimization, distribution system reconfiguration, renewable energy, stability index, binary particle swarm optimization, energi terbarukan, rekonfigurasi sistem distribusi, stability index.
Subjects:	T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK1087 Photovoltaic power generation T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK3030 Electric power distribution systems T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK5105.5956 Quality of service. Reliability Including network performance
Divisions:	Faculty of Intelligent Electrical and Informatics Technology (ELECTICS) > Electrical Engineering > 20201-(S1) Undergraduate Thesis
Depositing User:	Mochammad Naufal Hakim
Date Deposited:	30 Jul 2024 08:26
Last Modified:	30 Jul 2024 08:26
URI:	http://repository.its.ac.id/id/eprint/109950

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