Penentuan Beban Transformator Gardu Induk Rungkut Di Pt Pln (Persero) Untuk Menjaga Health Index Transformator

Estyandhika, Elyana (2021) Penentuan Beban Transformator Gardu Induk Rungkut Di Pt Pln (Persero) Untuk Menjaga Health Index Transformator. Masters thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Sebagai salah satu perusahaan yang bergerak dibidang kelistrikan, PLN harus mampu memberikan pasokan listrik kepada pelanggan. Proses bisnis kelistrikan di mulai dari Pembangkit, Transmisi dan distribusi. Sistem distribusi menerima tenaga listrik dari suatu sumber yaitu transmisi dengan menggunakan transformator dimana transformator bekerja sesuai dengan beban yang ada pada pelanggan. PT PLN (Persero) berupaya meningkatkan pelayanan dan penyediaan listrik di Indonesia termasuk di wilayah Jawa Timur. Untuk meningkatkan pelayanan, perlu dilakukan pemeliharaan aset peralatan. Dalam sistem distribusi aset peralatan yang dimiliki salah satunya adalah transformator. Menjaga Health Index Transformator melalui pembebanan sesuai standar yaitu 80% merupakan salah satu cara untuk menjaga agar aset peralatan tidak cepat rusak dan menjaga umur transformator. Untuk mengetahui beban, analisa dilakukan pada Transformator Gardu Induk Rungkut PT PLN (Persero) Jawa Timur yang memiliki banyak pelanggan industri. Analisis penentuan beban transformator tahun berikutnya akan dilakukan dengan menggunakan Time Series Regression dengan penentuan standar pembebanan transformator mengacu pada SE 0017 / E / DIR / 2014 yang berlaku untuk PLN. Dari hasil analisis penelitian ini dapat diperoleh prediksi pembebanan transformator untuk tahun depan yaitu tahun 2021 keadaan pembebanan transformator masih dalam kategori cukup sehingga apabila ada tambahan beban dari pemasangan baru pelanggan atau menambah daya, transformator masih mampu. ====================================================================================================== As a company engaged in electricity, PLN must be able to supply electricity to customers. The electricity business process starts from generation, transmission and distribution. The distribution system receives electricity from a source, namely transmission using a transformer where the transformer works according to the load on the customer. PT PLN (Persero) seeks to improve services and supply of electricity in Indonesia, including in the East Java region. To improve service, it is necessary to maintain equipment assets. In the distribution system of equipment assets owned, one of which is a transformer. Maintaining the Health Index Transformer through loading according to the standard of 80% is one way to keep equipment assets from being damaged quickly and to maintain the life of the transformer. To determine the load, the analysis was carried out at PT PLN (Persero) East Java's Rungkut Substation Transformer which has many industrial customers. The analysis for determining the transformer load for the following year will be carried out using Time Series Regression with the determination of the transformer loading standard referring to SE 0017 / E / DIR / 2014 which applies to PLN. From the results of this research analysis can be obtained prediction transformer loading for the next year, namely 2021 along with the state of the transformer and the condition of the transformer is still in the sufficient category so that if there is an additional load from installing new customers or adding power, the transformer is still capable.

Item Type: Thesis (Masters)
Uncontrolled Keywords: Forecasting, Electric Load,Time Series Regression, Peramalan , Pembebanan Transformator, Time Series Regresi
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK201 Electric Power Transmission
H Social Sciences > HA Statistics > HA30.3 Time-series analysis
Q Science > QA Mathematics > QA276 Mathematical statistics. Time-series analysis. Failure time data analysis. Survival analysis (Biometry)
Q Science > QA Mathematics > QA278.2 Regression Analysis. Logistic regression
T Technology > T Technology (General) > T174 Technological forecasting
Divisions: Faculty of Creative Design and Digital Business (CREABIZ) > Technology Management > 61101-(S2) Master Thesis
Depositing User: ELYANA ESTYANDHIKA
Date Deposited: 22 Feb 2021 04:58
Last Modified: 22 Feb 2021 04:58
URI: https://repository.its.ac.id/id/eprint/82686

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