Title: Application of a principal component regression for the electricity markets data
Authors: Leila Louhichi - Faculty of economic science and management of Sousse (Tunisia) [presenting]
Zied Kacem - Polytechnique Sousse (Tunisia)
salwa ben ammou - Faculty of Economic Science and Management of Sousse (Tunisia)
Abstract: Controlling energy consumption, particularly electricity consumption, is one of the pillars mentioned by the public authorities for implementing the energy transition. As a result, producing and consuming electricity in the residential sector is among the strategic objectives in Tunisia as a result of constraints related to the exploitation of existing energy sources. We will determine the factors that explain the electricity consumption in the residential sector. To do this, and to reduce the number of explanatory variables and solve the multi-colinearity problem of the variables used, we opted for principal component regression as a regression model. This principal component regression model (PCR) will be validated by an application on a set of regional data previously performed on variables initially correlated. Application of a principal component regression for the electricity markets data.