LAUSR

During the last decade, major changes have affected the electricity sector in Algeria. As consequence it recorded an important increase of electricity demand in energy and capacity under the mixt pressure of demography and socio-economic development, climate change, and the depletion of natural gas reserves which imposes new challenges in terms of renewable energies and demand side management. These adjustments enhanced the important role of electricity demand forecasting. The aim of this study is to construct the best overall model that represents the relationship between electricity demand and air temperature, i.e. heating and cooling degree days, and taking into consideration other deterministic variables. A simple multiple regression model has been developed, since it allows us to investigate this relationship in an easy and controlled manner. Additionally, the model can be used to forecast electricity demand for the next year on a daily basis. The results show that CDD and HDD have the highest effect on electricity demand, and can be seen as the main factors affecting the daily load in Algeria. On the other hand, holidays reduce electricity demand in all seasons. We also secluded the dummy representing the holy month of Ramadan where it was clear that the behavior during this holiday increased the electricity demand especially in the summer seasons.