Subsequently, the total GDP of Thailand has been projected with the help of the growth rates given in the Power Development Plan (PDP) developed by Electricity Generation Authority of Thailand (EGAT) [41] and the population growth rate has been determined with the help of past data (0.51% per annum growth rate from 2011 to 2050). Then, the population and value added for each industrial sub-sector is projected and this in turn helps determine the projection of energy consumption for each industrial sub-sector. Regression equations, in terms of their coefficients and coefficient of correlations (R2) are given in Table 1. This study makes use of two types of regression methods, namely the logarithmic regression and the multiple variable methods. The logarithmic method utilizes only a single variable, where it seems a better fit in terms of energy consumption than multiple variable methods. Likewise the energy demand projection for the respective sub-sectors for the years 2030 and 2050 are given in Table 2. The basis of using regression analysis is the underlying notion that the energy consumption of each sub-sector is correlated to the economic production of each sub-sector, which in turn is given and expressed as the economic value added by each sub-sector and the population to which each sub-sector should produce for. As it can be seen from Table 1, there is significant correlation between the factors and hence, this mathematical model has been used to project the future energy consumption of each sub-sector of the Thai industrial sector.