Operasi optimum stand-alone microgrid menggunakan metode self adaptive modified firefly algorithm dengan mempertimbangkan karakteristik umur baterai

Fitriana, Aprilely Ajeng (2015) Operasi optimum stand-alone microgrid menggunakan metode self adaptive modified firefly algorithm dengan mempertimbangkan karakteristik umur baterai. Masters thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Stand-alone microgrid merupakan sistem kelistrikan yang pasokan energi
listriknya didapatkan dari sumber energi terbarukan, distributed generation, dan
energy storage device tanpa terhubung dengan grid. Pada penelitian ini, operasi
stand-alone microgrid menggunakan photovoltaic (PV) dan wind turbine (WT)
sebagai pembangkit energi listrik pada sistem ini. Untuk mempertahankan utilitas
ketika PV dan WT tidak dapat memasok energi listrik, sistem ini menggunakan
baterai sebagai media penyimpanan energi dan diesel engine (DE) sebagai back-up.
Batasan SOC baterai diperhatikan dalam operasi sistem ini, baik pada kondisi
charging maupun discharging sehingga rugi umur baterai dapat diminimalkan.
Operasi optimum pada sistem ini digunakan untuk meminimalkan biaya
pembangkitan dan rugi umur baterai. Penyelesaian operasi optimum pada sistem ini
menggunakan metode self-adaptive modified firefly algorithm (SAMFA). Sebagai
pembanding metode ini, penyelesaian operasi optimum pada sistem ini
menggunakan firefly algorithm (FA) dan particle swarm optimization (PSO).
Berdasarkan simulasi, hasil operasi optimum menggunakan metode SAMFA
telah dibandingkan dengan PSO dan FA. Dari hasil tersebut, diketahui bahwa
metode SAMFA memiliki nilai fitness yang paling rendah bila dibandingkan
dengan FA dan PSO, yaitu 6,29 dengan total biaya pembangkitan sebesar
Rp4.164.718,53 dan rugi umur baterai 0,53% pada studi kasus I. Sedangkan pada
studi kasus II diperoleh nilai fitness sebesar 9,634 dengan total biaya pembangkitan
sebesar Rp8.472.157,31 dan rugi umur baterai sebesar 0,58%.

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Stand-alone microgrid is an electrical system that supplies electrical energy
obtained from renewable energy sources, distributed generation, and energy storage
device without connecting to the grid. In this research, operation of stand-alone
microgrid using photovoltaic (PV) and wind turbine (WT) as an electric energy
generator in this system. To maintain the utility when PV and WT cannot supply
electric energy, this system uses battery as energy storage medium and diesel engine
(DE) as a back-up. Boundary of SOC battery SOC noted in this system operation,
both the charging and discharging conditions. So, the battery life loss can be
minimized. Operation optimization of this system is used to minimize the
generation cost and battery life loss. Operation optimization solution on this system
using the method of self-adaptive algorithm modified firefly (SAMFA). As
comparison of this method, operation optimization solution of this system using the
firefly algorithm (FA) and particle swarm optimization (PSO).
Based on the simulation, operation optimization results using SAMFA method
has been compared by PSO and the FA. From these results, it is known that the
method SAMFA has the lowest fitness value than FA or PSO. In study case I, the
best fitness value result of this method is 6.29, Rp4,164,718.53 generation cost, and
0.53% life loss battery. In study case II, the best fitness value result of this method
is 9,634, Rp8,472,157.31 generation cost, and 0.58% life loss battery.

Item Type: Thesis (Masters)
Additional Information: RTE 333.793 Fit o
Uncontrolled Keywords: biaya pembangkitan, multiobjektif, rugi umur baterai, stand-alone microgrid, ================================================================================================ cost, multiobjective, life loss battery, stand-alone microgrid
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK1001 Production of electric energy or power
Divisions: Faculty of Electrical Technology > Electrical Engineering > 20101-(S2) Master Thesis
Depositing User: - Taufiq Rahmanu
Date Deposited: 01 Apr 2019 03:29
Last Modified: 01 Apr 2019 03:29
URI: http://repository.its.ac.id/id/eprint/62660

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