Predicting Electricity Consumption in the Kingdom of Saudi Arabia

Marwa Salah EIDin Fahmy, Farhan Ahmed, Farah Durani (), Štefan Bojnec () and Mona Mohamed Ghareeb
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Marwa Salah EIDin Fahmy: Sadat Academy for Management Sciences, Cairo 2222, Egypt
Farhan Ahmed: Department of Economics & Management Sciences, NED University of Engineering & Technology, Karachi 75270, Pakistan
Farah Durani: College of Business Administration, University of Business and Technology, Jeddah 21361, Saudi Arabia
Štefan Bojnec: Faculty of Management, University of Primorska, SI-6000 Koper-Capodistria, Slovenia
Mona Mohamed Ghareeb: Faculty of High Asian Studies, Zagazig University, Zagazig 31527, Egypt

Energies, 2023, vol. 16, issue 1, 1-20

Abstract: Forecasting energy consumption in Saudi Arabia for the period from 2020 until 2030 is investigated using a two-part composite model. The first part is the frontier, and the second part is the autoregressive integrated moving average (ARIMA) model that helps avoid the large disparity in predictions in previous studies, which is what this research seeks to achieve. The sample of the study has a size of 30 observations, which are the actual consumption values in the period from 1990 to 2019. The philosophy of this installation is to reuse the residuals to extract the remaining values. Therefore, it becomes white noise and the extracted values are added to increase prediction accuracy. The residuals were calculated and the ARIMA (0, 1, 0) model with a constant was developed both of the residual sum of squares and the root means square errors, which were compared in both cases. The results demonstrate that prediction accuracy using complex models is better than prediction accuracy using single polynomial models or randomly singular models by an increase in the accuracy of the estimated consumption and an improvement of 18.5% as a result of the synthesizing process, which estimates the value of electricity consumption in 2030 to be 575 TWh, compared to the results of previous studies, which were 365, 442, and 633 TWh.

Keywords: energy consumption; electricity consumption; prediction; Saudi Arabia (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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