Hydroelectricity consumption forecast for Pakistan using ARIMA modeling and supply-demand analysis for the year 2030

Rehan Jamil

Renewable Energy, 2020, vol. 154, issue C, 1-10

Abstract: The amount of electricity generation and its availability to the residents of a country reflects its level of development and economic condition. Water being one of the cheapest and renewable sources of energy, is being used to produce one-quarter of the total electricity production in Pakistan. This article presents a forecasting study of hydroelectricity consumption in Pakistan based on the historical data of past 53 years using Auto-Regressive Integrated Moving-Average (ARIMA) modeling. Based on the developed forecasting equation, the hydroelectricity consumption was predicted up to the year 2030. For validating the reliability of the forecasted data, the results were compared to the actual values which showed good fit with minimum deviation. The forecasted values of hydroelectricity consumption revealed an average annual increment of 1.65% with a cumulative increase of 23.4% up to the year 2030. The results were compared with the hydroelectricity generation plans of the Government of Pakistan for its effectiveness. A sensitivity analysis was also performed to study the relation of hydroelectricity consumption to the annual population and GDP growth rate of the country. The research shall significantly prove to be useful in better planning and management of water resources of Pakistan for future.

Keywords: Hydroelectricity consumption; ARIMA model; Time series forecasting; Hydropower; Renewable energy; Pakistan (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (20)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0960148120303128
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:154:y:2020:i:c:p:1-10

DOI: 10.1016/j.renene.2020.02.117

Access Statistics for this article

Renewable Energy is currently edited by Soteris A. Kalogirou and Paul Christodoulides

More articles in Renewable Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().