University of Bahrain
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Forecasting the Generation and Consumption of Electricity and Water in Kingdom of Bahrain using Grey Models

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dc.contributor.author Boopathi A, Manivanna
dc.contributor.author E A, Mohamed Ali
dc.contributor.author Velappan, Subha
dc.contributor.author A, Abudhahir
dc.date.accessioned 2020-08-05T12:53:04Z
dc.date.available 2020-08-05T12:53:04Z
dc.date.issued 2021-04-01
dc.identifier.issn 2210-142X
dc.identifier.uri https://journal.uob.edu.bh:443/handle/123456789/4057
dc.description.abstract Generation and consumption of Electricity and water are the key factors impacting the economy of any nation. Forecasting the future need of electricity and water can help the nation to plan its economy and future growth. This motivates to pursue a research to develop an efficient method to forecast the future need of Electricity and Water. In this paper, two Grey Models have been developed and employed to forecast the expected amount of generation and consumption of Electricity and Water in Kingdom of Bahrain by 2025. The past data of generation and consumption have been taken from the official statistics of Electricity and Water Authority of the Kingdom. The developed Grey Model and Modified Grey Model are used to forecast various factors such as Fuel Oil Consumption for Electricity Generation, Natural Gas Consumption for Electricity Generation, Electricity Consumption, Average Daily Production of Desalinated Water & Abstraction of Ground Water, Average Daily Water Consumption and Population for the year 2025. The results of experiments clearly show that the Kingdom is progressing towards achieving its Vision 2030. The accuracy of forecast is ensured by ensuring the least Mean Relative Percentage Error in forecasting. en_US
dc.language.iso en en_US
dc.publisher University of Bahrain en_US
dc.rights Attribution-NonCommercial-NoDerivatives 4.0 International *
dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/4.0/ *
dc.subject : Grey Model (1,1), Modified Grey Model (1,1), Grey Prediction, Mean Relative Percentage Error, Forecast accuracy en_US
dc.title Forecasting the Generation and Consumption of Electricity and Water in Kingdom of Bahrain using Grey Models en_US
dc.identifier.doi http://dx.doi.org/10.12785/ijcds/100139
dc.volume 10 en_US
dc.pagestart 1 en_US
dc.pageend 8 en_US
dc.source.title International Journal of Computing and Digital Systems en_US
dc.abbreviatedsourcetitle IJCDS en_US


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