Abstract:
Meteorological factors, particularly temperature, have a considerable influence
on the energy consumption of the Algerian population. Using two real databases,
one on temperatures and the other on electricity consumption, covering more
than eight consecutive years, the study examines seasonal variations and the
impact of temperature on energy demand. Before turning to prediction, a visual
analysis is performed to identify trends, using heat maps and time-series
graphs. The methodology relies on linear regression and artificial neural network
(ANN) models to predict electricity consumption, using temperature and
previous day's consumption as the main factors
