Forecasting Household Energy Consumption using LSTM Model

Authors

Bezzar Nour El Houda
Laboratoire de Mines, Larbi Tebessi University, Tebessa, Algeria
Meraoumia Abdallah
Laboratory of Mathematics, Informatics and Systems (LAMIS), University of Larbi Tebessi, Tebessa
Lotfi Houam
Laboratory of Mathematics, Informatics and Systems (LAMIS), University of Larbi Tebessi, Tebessa

Synopsis

The demand for energy, particularly electricity, has witnessed a recent global increase. Consequently, monitoring the evolution of energy consumption has become crucial. Energy consumption forecasting plays a pivotal role in utility load planning and electricity demand management. This paper aims to propose a prediction model for household electricity consumption using LSTM. The obtained results demonstrate that the proposed model exhibits feasible and reliable performance, demonstrating sufficient accuracy in predicting energy consumption, particularly in terms of hourly and daily accuracy.

ICAECE2023
Published
February 5, 2024