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PERBANDINGAN PREDIKSI BEBAN MENGGUNAKAN METODE REGRESI NON LINEAR EKSPONENSIAL DAN DOUBLE EXPONENTIAL SMOOTHING PADA TRANSFORMATOR DAYA 20 MVA GARDU INDUK SUNGAI JUARO PT. PLN (PERSERO)

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Transformers have a very important role in the electrical power system. Specifically, transformers are used to change the voltage level, either to step up or step down the voltage. Predicting the load on a transformer is very important to keep the system reliable and to avoid overloading in the coming years. This research aims to forecast the load on a 20 MVA Power Transformer at the Sungai Juaro Substation of PT. PLN (Persero) for the period of 2025–2034 and to compare two load forecasting methods: Nonlinear Exponential Regression and Double Exponential Smoothing. The data used are the average annual peak loads from 2020 to 2024, with a prediction period of 10 years (2025–2034). The evaluation uses the Mean Absolute Percentage Error (MAPE) to measure the accuracy of each method. The results show that the predicted load using Nonlinear Exponential Regression in 2034 is 23.6890 MVA, which is 118.45% of the transformer's capacity, while the predicted load using Double Exponential Smoothing in 2034 is 17.6130 MVA, or 88.07%. The results also show that the Nonlinear Exponential Regression method has a lower MAPE value of 3.85%, so it can be concluded that this method gives a more accurate prediction. The prediction shows that the transformer load is expected to exceed its nominal capacity of 20 MVA by 2034. Therefore, transformer replacement should be considered to maintain the reliability of the electrical system. Keywords: Load forecasting, Power transformer, Exponential Non Linear Regression, Double Exponential Smoothing, MAPE.

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Inventory Code Barcode Call Number Location Status
2507003482T175849T1758492025Central Library (Reference)Available but not for loan - Not for Loan
Detail Information
Series Title
-
Call Number
T1758492025
Publisher
Indralaya : Prodi Teknik Elektro, Fakultas Teknik Universitas Sriwijaya.,
Collation
xiv, 72 hlm.; ilus.; tab.; 29 cm.
Language
Indonesia
ISBN/ISSN
-
Classification
621.310 7
Content Type
Text
Media Type
-
Carrier Type
-
Edition
-
Subject(s)
Teknik elektro
Specific Detail Info
-
Statement of Responsibility
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