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)

PERMATASARI, SHERLINA and Adipradana, Wirawan (2025) 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). Undergraduate thesis, Sriwijaya University.

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Abstract

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.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Keywords: Load forecasting, Power transformer, Exponential Non Linear Regression, Double Exponential Smoothing, MAPE.
Subjects:	T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK3001-3521 Distribution or transmission of electric power
Divisions:	03-Faculty of Engineering > 20201-Electrical Engineering (S1)
Depositing User:	Sherlina Permatasari
Date Deposited:	23 Jun 2025 02:57
Last Modified:	23 Jun 2025 02:57
URI:	http://repository.unsri.ac.id/id/eprint/175849

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