ESTIMASI BEBAN PUNCAK ENERGI LISTRIK PADA SISTEM SULUTGO MENGGUNAKAN ARTIFICIAL NEURAL NETWORK DAN METODE MOVING AVERAGE
ABSTRACT: Sulutgo
interconnection system is the electrical energy suppliers for North Sulawesi
and Gorontalo. Their role as the electrical energy supplier was complained by
people in 2015, due to lack of electricity supply that lead to continuous
rolling blackouts. Accordingly, it is important to identify the electrical peak
load in Sulutgo system, so that the electrical necessity of the people can be
properly fulfilled.
The electrical peak load in the next 12 month is estimated using the
backpropagation method artificial neural network and forecasting method moving
average. The estimation was performed by using the last 24 month peak load
data.
Based on the results of both estimation, it is found the backpropagation
method artificial neural network has fluctuated results while the forecasting
method moving average gives stable results.
The results of the estimation of peak load electricity using
bacpropagation artificial neural network
method for the next 12 month starting from July 2016 to June 2017 are 327.48,
353.99, 316.32, 316.66, 332.37, 329.79, 332.31, 356.21, 318.60, 349.56, 351.37,
362.04 MW. While the results of the estimation method using moving average forecasting
for the same period are 325.68, 326.03, 326.39, 326.72, 327.25, 328.09, 327.94,
328.72, 329.94, 330.32, 327.65, 326.52 MW.
Penulis: Liberty Tarigan,
Tritiya Arungpadang, Johan S C Neyland
Kode Jurnal: jptmesindd160220
