SIMULASI PREDIKSI BEBAN ENERGI LISTRIK AREA PELAYANAN JARINGAN KABUPATEN KENDAL TAHUN 2021-2026 MENGGUNAKAN METODE RADIAL BASIS FUNCTION

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TitleSIMULASI PREDIKSI BEBAN ENERGI LISTRIK AREA PELAYANAN JARINGAN KABUPATEN KENDAL TAHUN 2021-2026 MENGGUNAKAN METODE RADIAL BASIS FUNCTION
AuthorHerdika Kurnia Ramadhan
AbstractABSTRACT

Electricity consumption prediction is an attempt to estimate future electricity usage based on pre-existing electricity consumption data. One method that can be used to solve prediction problems is the Radial Basis Function (RBF), which is one of the methods of artificial neural networks (ANN). The purpose of this final project is to estimate the load of electrical energy in the Kendal Regency Network Service Area using the Radial Basis Function.One of the predictions of this electrical load can be done using the Radial Basis Function Artificial Neural Network (ANN) method. This method uses training data learning from 2013 - 2020 as a reference data. Calculations with this method are based on empirical experience of electricity provider planning which is relatively difficult to do, especially in terms of co rrec- tions that need to be made to changes in load. This study specifically predicts the electricity load in the Kendal Rayon network service area in 2021-2026. The results of this Artificial Neural Network produce projected electricity demand needs in 2021-2026 with an average annual increase of 1.01% and peak load in 2021-2026. The highest peak load in 2024 and the dominating average is the household sector with an increase of 1% per year. The accuracy results of the Radial Basis Function model reached 90%.
KeywordsSimulations, Matlab, Electrical Loads, Predictions, Radial Basis Function Models
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Issn2302-0709
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Viewed237
Created At7 Des 2021 18.55.20