Modelling and Forecasting of Residential Electricity Consumption in Nigeria Using Multiple Linear Regression Model and Quadratic Regression Model with Interactions

Abstract

In this paper statistical analysis of residential electricity demand in Nigeria is presented. Multiple linear regression model and quadratic regression model with interactions are applied to estimate residential electricity consumption and to forecast long-term residential electricity demand in Nigeria. Population and temperature are used as explanatory variables. The results show the Quadratic Regression with interaction has RMSE of 52.77 and r-square value of 0.9389 which indicates that 93.89% of the variation in residential electricity consumption is explained by the model. On the other hand , the multiple linear regression model has RMSE of 69.97 and r-square value of 0.873 which indicates that 87.3% of the variation in residential electricity consumption is explained by the model. Essentially, the quadratic regression model with interaction with lower RMSE and higher r-square value is selected and then used to forecast the residential electricity demand in Nigeria from 2015 to 2029. From the results, the Residential Electricity Consumption in Nigeria will reach 6521.09 MW/h in the year 2029. Furthermore, the results show that population has a positive sign and it is significant in the short run and in the long run forecasting. On the other hand, the result also revealed insignificant moderately weak relationship between residential electricity consumption and temperature.

Keywords

• Electricity
• Multiple Linear Regression Model
• Quadratic Regression Model
• Regression Model with Interactions
• Statistical Analysis
• Forecasting of Residential Electricity Demand