PERAMALAN BEBAN LISTRIK JANGKA MENENGAH PADA SISTEM KELISTRIKAN KOTA SAMARINDA
Abstract: Demand of electric
power in Samarinda continuously increasing in line with development of
Samarinda city. To fill the demand of electricity in the future at a certain
period, it is necessary to know precisely the demand for electricity in the
certain period. This research has been carried out mid-term electric load
forecasting electricity system in Samarinda using Artificial Neural Network
(ANN). This method is an excellent method for finding non-linear relationship
between load with economic factors are varied, and can make adjustments to the
changes.The result of this study indicates that the selection of parameters
such as the learning method, the number of neurons, hidden layer and influence
the accuracy of forecasting the electrical load. From the results of electric
power load forecasting medium term Samarinda MSE values obtained by 6,9134E +
03, using the parameters training and network configuration [7-70-1]. Retrieved
peak load in 2020 amounted to 741 MW, close to the electrical plan of PT. PLN
(Persero) amounting to 718 MW. In the electricity load forecasting is well
known that the annual burden will increase.
Penulis: Muslimin
Kode Jurnal: jptindustridd150618
