Pembangkitan Ekonomis pada Unit Pembangkit Listrik Tenaga Diesel Telaga Gorontalo Menggunakan Algoritma Genetika

The increasing daily need towards electrical energy demands for generation companies to conduct operational cost-saving strategy including the generation fuel.  One of the strategies that can be done is through economical generation optimization.  The genetics algorithm of the heuristics method is k...

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Main Author: Sabhan Kanata
Format: Article
Language:English
Published: Universitas Syiah Kuala 2017-12-01
Series:Jurnal Rekayasa Elektrika
Subjects:
Online Access:http://www.jurnal.unsyiah.ac.id/JRE/article/view/5451
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author Sabhan Kanata
author_facet Sabhan Kanata
author_sort Sabhan Kanata
collection DOAJ
description The increasing daily need towards electrical energy demands for generation companies to conduct operational cost-saving strategy including the generation fuel.  One of the strategies that can be done is through economical generation optimization.  The genetics algorithm of the heuristics method is known for its ability to overcome the problems characterized as non-linear, non convex,   integer/ discrete, not continuous,  and a system with a lot of variables.  The evaluation technique employing the evolution theory has been applied to the case of IEEE 26 buses power system and diesel power generation in a unit in Telaga, Gorontalo.  The result shows that the proposed method is believed to be able to minimize the generation cost better than the previous method.   The method is tested by applying for its real system in Telaga, Gorontalo and it is found that the total cost at Rp 20.201.000,00 per hour with total load at 5.000 kW.
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spelling doaj.art-5f507e5b4e694aaebda188add277ea532022-12-22T02:44:13ZengUniversitas Syiah KualaJurnal Rekayasa Elektrika1412-47852252-620X2017-12-0113311912410.17529/jre.v13i3.54517172Pembangkitan Ekonomis pada Unit Pembangkit Listrik Tenaga Diesel Telaga Gorontalo Menggunakan Algoritma GenetikaSabhan Kanata0Jurusan Teknik Elektro Fakultas Teknik Universitas Ichsan GorontaloThe increasing daily need towards electrical energy demands for generation companies to conduct operational cost-saving strategy including the generation fuel.  One of the strategies that can be done is through economical generation optimization.  The genetics algorithm of the heuristics method is known for its ability to overcome the problems characterized as non-linear, non convex,   integer/ discrete, not continuous,  and a system with a lot of variables.  The evaluation technique employing the evolution theory has been applied to the case of IEEE 26 buses power system and diesel power generation in a unit in Telaga, Gorontalo.  The result shows that the proposed method is believed to be able to minimize the generation cost better than the previous method.   The method is tested by applying for its real system in Telaga, Gorontalo and it is found that the total cost at Rp 20.201.000,00 per hour with total load at 5.000 kW.http://www.jurnal.unsyiah.ac.id/JRE/article/view/5451Economic dispatchIEEE 26 busTelaga power plantgenetic algorithm
spellingShingle Sabhan Kanata
Pembangkitan Ekonomis pada Unit Pembangkit Listrik Tenaga Diesel Telaga Gorontalo Menggunakan Algoritma Genetika
Jurnal Rekayasa Elektrika
Economic dispatch
IEEE 26 bus
Telaga power plant
genetic algorithm
title Pembangkitan Ekonomis pada Unit Pembangkit Listrik Tenaga Diesel Telaga Gorontalo Menggunakan Algoritma Genetika
title_full Pembangkitan Ekonomis pada Unit Pembangkit Listrik Tenaga Diesel Telaga Gorontalo Menggunakan Algoritma Genetika
title_fullStr Pembangkitan Ekonomis pada Unit Pembangkit Listrik Tenaga Diesel Telaga Gorontalo Menggunakan Algoritma Genetika
title_full_unstemmed Pembangkitan Ekonomis pada Unit Pembangkit Listrik Tenaga Diesel Telaga Gorontalo Menggunakan Algoritma Genetika
title_short Pembangkitan Ekonomis pada Unit Pembangkit Listrik Tenaga Diesel Telaga Gorontalo Menggunakan Algoritma Genetika
title_sort pembangkitan ekonomis pada unit pembangkit listrik tenaga diesel telaga gorontalo menggunakan algoritma genetika
topic Economic dispatch
IEEE 26 bus
Telaga power plant
genetic algorithm
url http://www.jurnal.unsyiah.ac.id/JRE/article/view/5451
work_keys_str_mv AT sabhankanata pembangkitanekonomispadaunitpembangkitlistriktenagadieseltelagagorontalomenggunakanalgoritmagenetika