evaluation of power systems reliability using an artificial neural network
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8/9/2019 EVALUATION OF POWER SYSTEMS RELIABILITY USING AN ARTIFICIAL NEURAL NETWORK
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SUMMARY
EVALUASI KEANDALAN SISTEM TENAGA LISTRIK MENGGUNAKAN
JARINGAN SYARAF TIRUAN
EVALUATION OF POWER SYSTEMS RELIABILITY USING AN ARTIFICIAL NEURAL NETWORKCreated by JOKO PITONO
Subject : sistem tenaga listrik
Keyword : : Evaluasi Keandalan; Sistem Transmisi; Unit Pembangkit; Jaringan Syaraf Tiruan.; ReliabilityEvaluation; Transmission System; Generating Unit; Artificial Neural Network
Description :
Kelayakan dan keselamatan sistem tenaga listrik merupakan bagian yang sangat penting dalam analisis-analisis
keandalan, oleh karena itu dua hal di atas selalu dipakai sebagai obyek para evaluator keandalan sistem tenaga listrik.
Mengevaluasi keandalan sistem tenaga listrik menggunakan Jaringan Syaraf Tiruan (JST) merupakan metoda baru yangdapat memecahkan kesulitan-kesulitan pada metoda-metoda analisis keandalan sebelumnya yang membutuhkan
pemodelan yang komplek dan komputasi yang besar. Dengan atau tanpa perubahan yang memungkinkan dilakukanya
penyesuaian dengan data lapangan yang diperoleh pada pengelola sistem tenaga listrik di Indonesia,
parameter-parameter yang digunakan pada sistem pembangkit adalah scheduled maintenace, Mean Time To Failure
(MTTF), Mean Time To Repaire (MTTR) dan forced outage rate, sedangkan parameter-parameter yang digunakan pada
sistem transmisi adalah transient outage rate, permanent outage rate, permanent outage duration, normal rating, long
term dan short term rating. Suatu perkembangan pemikiran yang mengacu pada issue otonomi daerah dan suastanisasi
kelistrikan di Indonesia, maka kegiatan Evaluasi Keandalan Sistem Tenaga Listrik merupakan kegiatan awal yang
sangat penting sebelum mengambil keputusan-keputusan selanjutoya.
Description Alt:
Adequacy and security system are important part in reliability analysis, therefore the both (adequacy and security)
always used by the evaluator of power system reliability. Evaluate of power system reliability using an artificial neural
network is a new method which can solve difficulties of the previous reliability analysis methods, such as complex
modelling and large computations. By adapting to the validity of the real data in Indonesia, for reliability evaluation of
the generation system used four parameters. In this manner, four parameters are scheduled maintenace, Mean Time To
Failure (MTTF), Mean Time To Repaire (MTTR) and forced outage rate. For reliability evaluation of the transmision
system, six parameters are needed. The six parameters are transient outage rate, permanent outage rate, permanent
outage duration, normal rating, long term and short. An improvement thinking that focus to issue regional autonomy and
private electricity in Indonesia, evaluation of power system reliability is an important starting activity before take
forward decision.
Contributor : Dr. Ir. Mauridhi Hery Purnomo, M.Eng.
Prof. Dr. Ir. H. Ontoseno Penangsang, M.Sc.Date Create : 23/12/2006
Type : Text
Format : pdf ; 104 pages
Language : Indonesian
Identifier : ITS-Master-3100003018397
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Collection : 3100003017907
Call Number : 006.32 Jok e
Source : Theses Electrical Engineering RTE 006.32 Jok e, 2003
COverage : ITS Community
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