Rachmad, Basuki (2016) Genetic Algorithm Untuk Penyelesaian Optimal Power Flow Pada Sistem Distribusi Radial Mempertimbangkan DG. Undergraduate thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Dalam perkembangan sistem tenaga listrik, sistem distribusi
listrik menjadi semakin luas dan kompleks sehingga menyebabkan rugirugi
yang terjadi pada sistem menjadi lebih besar. Untuk mengatasi hal
tersebut, cara yang umum dilakukan adalah dengan pemberian
Distributed Generation (DG) yang tepat. Pada tugas akhir ini, diusulkan
penyelesaian optimisasi aliran daya pada sistem distribusi dengan lokasi
dan ukuran DG secara simultan untuk memperoleh minimum rugi saluran,
minimum perubahan tegangan, dan menaikkan keluaran daya aktif DG.
Dan untuk menyelesaikan permasalahan sedemikian tidak konveks,
Genetic Algorithm (GA) metode yang diusulkan, yang mana mendekati
iterative optimisasi aliran daya.
Hasil simulasi kasus sistem IEEE 33 bus didapatkan aliran daya
optimal saat diinjeksi DG dengan nilai pembobotan fungsi objektif yang
seimbang untuk kerugian jaring dan deviasi tegangan. Total kerugian
jaring menjadi (22,173 kW) turun 89,06% dari nilai awal dan total deviasi
tegangan menjadi (-0,1652). Hasil simulasi kasus sistem IEEE 69 bus
didapatkan aliran daya optimal saat diinjeksi DG dengan nilai
pembobotan fungsi objektif yans seimbang untuk kerugian jaring dan
deviasi tegangan. Total kerugian jaring menjadi (13,188 kW) turun 94,1%
dari nilai awal dan total deviasi tegangan menjadi (-0,0012).
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In the development of electric power systems, electrical
distribution systems become increasingly extensive and complex, causing
losses that occur on the system becomes greater. To overcome this, the
common way is the provision of Distributed Generation (DG) is
appropriate. In this thesis, the proposed completion of the optimization of
power flow in the distribution system with location and sizing DG
simultaneously to obtain the minimum channel loss, minimum voltage
changes, and increase the active power output of DG. To solve such
problems are not convex, Genetic Algorithm (GA) method is proposed,
which approached the iterative optimization of the power flow.
The simulation results of IEEE 33 bus system case obtained
optimal power flow when injected DG with objective function value equal
weighting for network loss and voltage deviation. Total network loss
become (22,137 kW) decrease 89,06% of the initial value and the total
voltage deviation becomes (-0,1652). The simulation result of IEEE 69
bus system case obtained optimal power flow when injected DG with
objective function value equal weighting for network loss and voltage
deviation. Total network loss become (13,188 kW) decrease 94,1% of the
initil value and the total voltage deviation become (-0,0012).
Item Type: | Thesis (Undergraduate) |
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Additional Information: | RSE 621.319 Rac g |
Uncontrolled Keywords: | Jaringan Distribusi Listrik, Kerugian Jaring, Deviasi Tegangan, Genetic Algorithm (GA), Distributed Generation (DG). |
Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK3030 Electric power distribution systems |
Divisions: | Faculty of Industrial Technology > Electrical Engineering > 20201-(S1) Undergraduate Thesis |
Depositing User: | ansi aflacha |
Date Deposited: | 17 Feb 2020 02:09 |
Last Modified: | 17 Feb 2020 02:09 |
URI: | http://repository.its.ac.id/id/eprint/74960 |
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