A Study on the Fuel Consumption Demands of the Jordanian Residential Sector

Fuel consumption analysis has become crucial for the local government of Jordan and decision makers for securing economic stability and environmental protection. The current study employs an Artificial Neural Network (ANN) to analyze and estimate fuel use and demand in Jordan's residential sector. Throughout the investigation, five criteria are assessed: population (P), income level (IL), electricity unit price (E$), fuel unit price (F$), and ambient temperature (AT). From 1985 to 2020, data on fuel use and independent variables are gathered from official government reports and literature sources. Therefore, ANN is used to model, to analyze and estimate fuel use and demand in Jordan's residential sector. The results of this study showed that in the Jordanian residential sector fuel demands are mainly driven by the population and fuel price. Additionally, the present ANN model findings accuracy outperforms the literature models. Thus, the current ANN model is combined with time series analysis to forecast the fuel demands in Jordan's household sector for the next decade. The findings of this study are expected to be helpful for the decision makers in the country for developing reliable and productive planning for future energy policies in the household sector..