Electricity consumption and associated GHG emissions of the Jordanian industrial sector: Empirical analysis and future projection

Abstract

In this paper, an empirical model is developed for electricity consumption of the Jordanian industrial sector based on multivariate linear regression to identify the main drivers behind electricity consumption. In addition, projection of electricity consumption for the industrial sector based on time series forecasting is presented. It was found that industrial production outputs and capacity utilization are the two most important variables that affect demand on electrical power and the multivariate linear regression model can be used adequately to simulate industrial electricity consumption with very high coefficient of determination. To illustrate the importance of integrating energy efficiency within national energy plans, the impact of implementing high-efficiency motors was investigated and found to be significant. Without such basic energy conservation and management programs, electricity consumption and associated GHG emissions for the industrial sector are predicted to rise by 63% in the year 2019. However, if these measures are implemented on a gradual basis, over the same period, electricity consumption and GHG emissions are forecasted to ascend at a lower rate with low/no cost actions.