PERAMALAN BEBAN PUNCAK RATA-RATA PADA PENYULANG DAUHWARU SAMPAI TAHUN 2024
Total View This Week0
Total View This Week0
Institusion
Institut Teknologi Perusahaan Listrik Negara
Author
Eka Prastya, I Putu Yasa
Pahiyanti, Novi Gusti
Pawenary, Pawenary
Pahiyanti, Novi Gusti
Pawenary, Pawenary
Subject
Teknik Elektro
Datestamp
2022-10-11 04:47:53
Abstract :
Along with the development of the times and technology, which makes people's dependence on the use of electrical energy will also increase. The development of electricity needs of course must be balanced with the provision of electrical energy from PT. PLN (persero). One way that can be done is by forecasting the needs of electrical energy and electricity burden of the household sector in the next few periods. Forecasting of electrical energy needs is carried out as one of the guidelines for planning the development of the electricity industry in Indonesia in the policy making of electrical energy planning. In a forecasting it is unlikely that the predicted value is perfect, there will always be mistakes that are influenced by other factors. Choosing the right method can minimize the error value generated by a method used. In this study, forecasting was conducted using ARIMA (Autoregresion Integrated Moving Average) method. Where forecasters are only racing against historical data on the average peak load data of Dauhwaru refiners in 2018 and 2019. So the results obtained using the ARIMA method consisting of 3 stages, namely, the identification stage, the testing stage and the implementation stage, which in this study we get the best ARIMA model that is (2,1,1) which has the results of forecasting in the form of an increase in the average peak load with mape value obtained is 7.61% which can still be said to be good results for the results of a forecast
Along with the development of the times and technology, which makes people's dependence on the use of electrical energy will also increase. The development of electricity needs of course must be balanced with the provision of electrical energy from PT. PLN (persero). One way that can be done is by forecasting the needs of electrical energy and electricity burden of the household sector in the next few periods. Forecasting of electrical energy needs is carried out as one of the guidelines for planning the development of the electricity industry in Indonesia in the policy making of electrical energy planning. In a forecasting it is unlikely that the predicted value is perfect, there will always be mistakes that are influenced by other factors. Choosing the right method can minimize the error value generated by a method used. In this study, forecasting was conducted using ARIMA (Autoregresion Integrated Moving Average) method. Where forecasters are only racing against historical data on the average peak load data of Dauhwaru refiners in 2018 and 2019. So the results obtained using the ARIMA method consisting of 3 stages, namely, the identification stage, the testing stage and the implementation stage, which in this study we get the best ARIMA model that is (2,1,1) which has the results of forecasting in the form of an increase in the average peak load with mape value obtained is 7.61% which can still be said to be good results for the results of a forecast
Download
book
BibTex
Latex, Jabref
cloud_download
Original Resource
url resource Institution
