المجلة الدولية للاداء الاقتصادي
Volume 6, Numéro 1, Pages 78-88
2023-06-04
Authors : Sahed Abdelkader . Kahoui Hacene .
Forecasting electricity consumption is necessary for electric grid operation and utility resource planning, as well as to improve energy security and grid resilience. Thus, this research aims to investigate the prediction performance of the ARIMA and LSTM neural network model using electricity consumption data during the period 1990 to 2020. The time series for electricity consumption is divided into 70% for training data and 30% for test data. The results showed that the LSTM model provided improved forecasting accuracy than the ARIMA model.
Electricity Consumption ; ARIMA ; LSTM ; Algeria
Chekouri Sidi Mohammed
.
Sahed Abdelkader
.
pages 247-261.
Boulkroun Fouad
.
pages 2100-2124.
Touati Karima
.
Keddari Nassim
.
pages 512-535.
Gourine B
.
pages 139-160.
Bouabdallah Salah
.
pages 557-571.