Prediksi Tegangan Flashover pada Isolator Porselen 150 kV Terkontaminasi Alami Menggunakan Metoda Nonlinear Autoregressive Exogenous Neural Network (NARX-NN)

Mardini, Hasanah (2024) Prediksi Tegangan Flashover pada Isolator Porselen 150 kV Terkontaminasi Alami Menggunakan Metoda Nonlinear Autoregressive Exogenous Neural Network (NARX-NN). Masters thesis, Universitas Andalas.

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Abstract

Contaminants on insulators can degrade their performance and lead to flashovers, which disrupt the reliability of electrical power systems. This research aims to develop a neural network model for predicting flashover voltage on high-voltage porcelain insulators that have been naturally contaminated. Experimental tests were conducted to collect data on parameters such as temperature, humidity, contaminant levels (ESDD and NSDD), and flashover voltage. A Nonlinear Autoregressive Exogenous (NARX) neural network model was used to predict flashover voltage based on the input parameters obtained from the tests. The results demonstrate that the NARX model has a high correlation coefficient of 1, indicating 100% accuracy and excellent prediction capability. This model has the potential to be used for determining flashover voltage on naturally contaminated insulators in a non-destructive manner, supporting preventive maintenance scheduling and ultimately improving the reliability of electrical power systems.

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