Back to Search
Start Over
Forecast for the Cameroon’s Residential Electricity Demand Based on the Multilinear Regression Model
- Source :
- Energy and Power Engineering. 12:182-192
- Publication Year :
- 2020
- Publisher :
- Scientific Research Publishing, Inc., 2020.
-
Abstract
- The electricity needs of populations in Cameroon are increasing and are still very inadequate. Companies, public buildings and households are facing frequent blackout which constrain development and social well-being. Therefore, the present work tried to forecast the electricity demand in the residential sector in Cameroon, in order to contribute significantly to the mastery of electricity consumption and highlight decision-makers in this sector. Six macroeconomics parameters covering the period 1994-2014 are used for these issues. Stationarity tests within gross domestic product, gross domestic product per capita, electricity consumption, population and numbers of subscribers and households respectively; reveal that all the series are I(1). Thus, the VAR (Vector Autoregressive) model has been retained to forecast the electricity demand until 2020. The cusum test and the cusum of squared test attest the stability of that model with a margin of error of 0.02%. Previsions are then more reliable and show that the electric request will skip from 1721 GWh in 2014 to more than 2481 GWh in 2020 approximatively, following a growing yearly rate of 5.36%. In order to reach its emergence, Cameroon ought to speed up its production in the domain of hydroelectric and thermal grid in order to meet the requirements in electric power in short and long term.
- Subjects :
- Consumption (economics)
education.field_of_study
business.industry
020209 energy
020208 electrical & electronic engineering
Population
02 engineering and technology
Gross domestic product
Vector autoregression
Hydroelectricity
0202 electrical engineering, electronic engineering, information engineering
Per capita
Economics
Econometrics
Electricity
Electric power
business
education
Subjects
Details
- ISSN :
- 19473818 and 1949243X
- Volume :
- 12
- Database :
- OpenAIRE
- Journal :
- Energy and Power Engineering
- Accession number :
- edsair.doi...........707bfb74a4ddbd65105224749e4041a6