Mathematical modeling of Ethiopia's energy demand by sectors and energy types, with forecasts for the next 30 years

Due to the scarcity of economic resources, it is vital to optimize everything so that the supply and demand lines intersect in an optimized quantity, with no shortage or surplus of a provided item or service. Energy supply contains both surplus and shortage, thus estimating the amount of projected e...

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Main Authors: Arkbom Hailu Asfaw, Geremew Teklu, Antigen Birhan, Yiheyis Eshetu, Ebisa Regasa, Tinsae Wondimu
Format: Article
Language:English
Published: Elsevier 2024-11-01
Series:Heliyon
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Online Access:http://www.sciencedirect.com/science/article/pii/S2405844024162160
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author Arkbom Hailu Asfaw
Geremew Teklu
Antigen Birhan
Yiheyis Eshetu
Ebisa Regasa
Tinsae Wondimu
author_facet Arkbom Hailu Asfaw
Geremew Teklu
Antigen Birhan
Yiheyis Eshetu
Ebisa Regasa
Tinsae Wondimu
author_sort Arkbom Hailu Asfaw
collection DOAJ
description Due to the scarcity of economic resources, it is vital to optimize everything so that the supply and demand lines intersect in an optimized quantity, with no shortage or surplus of a provided item or service. Energy supply contains both surplus and shortage, thus estimating the amount of projected energy demand is a key work that must be completed. The objective of this paper is generating a mathematical model based on the actual data for thirty years forecasting. To create a mathematical model using actual data from the last fifteen years, a model that can represent the past trend and be used for future forecasting. This study provides a general overview of Ethiopia's current energy requirement with different energy type as well as sector-specific energy demand and estimates for different economic growth scenarios up to 2052. This model was created using a linear regression polynomial fit through Origin graphic and analysis software, and an econometric model was also applied. GDP was utilized as an independent variable in the economic model to determine the trend of energy consumption. Another input-output model is also used for multilinear regression to evaluate the change of four variables, GDP, population growth, urbanization growth rate, and general inflation rate, which was quantitatively linked with total energy requirement using Weka software. The mathematical model developed through linear and multilinear regression has been validated by using a different assumption on GDP growth based on past growth rate as low, medium and high growth rate and using the mathematical formula to generate an energy demand trend that can be compared with the actual trend; as a result, all the mathematical model that are generated has been found to be valid for the purpose of the intended work. Based on the generated mathematical model and different GDP growth rate scenario as low, medium, business as usual (BAU) and high a future energy demand was forecasted up to 2052 for thirty years. The model's results can help energy planners ensure that the country's supply capacity keeps up with predicted energy demand growth.
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spelling doaj-art-cf1f46540da145498ec6cc25a6c66e692025-08-20T02:07:31ZengElsevierHeliyon2405-84402024-11-011022e4018510.1016/j.heliyon.2024.e40185Mathematical modeling of Ethiopia's energy demand by sectors and energy types, with forecasts for the next 30 yearsArkbom Hailu Asfaw0Geremew Teklu1Antigen Birhan2Yiheyis Eshetu3Ebisa Regasa4Tinsae Wondimu5Sustanable Energy Center of Excellence, Addis Ababa Science and Technology University, P.O. Box 16417, Addis Ababa, Ethiopia; Nuclear Technology Center of Excellence, Addis Ababa Science and Technology University, P.O. Box 16417, Addis Ababa, Ethiopia; Department of Environmental Engineering, College of Engineering, Addis Ababa Science and Technology University, P.O. Box 16417, Addis Ababa, Ethiopia; College of Natural and Social Science, Addis Ababa Science and Technology University, P.O. Box 16417, Addis Ababa, Ethiopia; Corresponding author. Sustanable Energy Center of Excellence, Addis Ababa Science and Technology University, P.O. Box 16417, Addis Ababa, Ethiopia.Sustanable Energy Center of Excellence, Addis Ababa Science and Technology University, P.O. Box 16417, Addis Ababa, Ethiopia; College of Natural and Social Science, Addis Ababa Science and Technology University, P.O. Box 16417, Addis Ababa, EthiopiaSustanable Energy Center of Excellence, Addis Ababa Science and Technology University, P.O. Box 16417, Addis Ababa, Ethiopia; College of Natural and Social Science, Addis Ababa Science and Technology University, P.O. Box 16417, Addis Ababa, EthiopiaMinistry of Water and Energy, Addis Ababa, EthiopiaMinistry of Water and Energy, Addis Ababa, EthiopiaMinistry of Water and Energy, Addis Ababa, EthiopiaDue to the scarcity of economic resources, it is vital to optimize everything so that the supply and demand lines intersect in an optimized quantity, with no shortage or surplus of a provided item or service. Energy supply contains both surplus and shortage, thus estimating the amount of projected energy demand is a key work that must be completed. The objective of this paper is generating a mathematical model based on the actual data for thirty years forecasting. To create a mathematical model using actual data from the last fifteen years, a model that can represent the past trend and be used for future forecasting. This study provides a general overview of Ethiopia's current energy requirement with different energy type as well as sector-specific energy demand and estimates for different economic growth scenarios up to 2052. This model was created using a linear regression polynomial fit through Origin graphic and analysis software, and an econometric model was also applied. GDP was utilized as an independent variable in the economic model to determine the trend of energy consumption. Another input-output model is also used for multilinear regression to evaluate the change of four variables, GDP, population growth, urbanization growth rate, and general inflation rate, which was quantitatively linked with total energy requirement using Weka software. The mathematical model developed through linear and multilinear regression has been validated by using a different assumption on GDP growth based on past growth rate as low, medium and high growth rate and using the mathematical formula to generate an energy demand trend that can be compared with the actual trend; as a result, all the mathematical model that are generated has been found to be valid for the purpose of the intended work. Based on the generated mathematical model and different GDP growth rate scenario as low, medium, business as usual (BAU) and high a future energy demand was forecasted up to 2052 for thirty years. The model's results can help energy planners ensure that the country's supply capacity keeps up with predicted energy demand growth.http://www.sciencedirect.com/science/article/pii/S2405844024162160Energy demand forecastingEconometric modelInput output modelLinear regressionPolynomial fit
spellingShingle Arkbom Hailu Asfaw
Geremew Teklu
Antigen Birhan
Yiheyis Eshetu
Ebisa Regasa
Tinsae Wondimu
Mathematical modeling of Ethiopia's energy demand by sectors and energy types, with forecasts for the next 30 years
Heliyon
Energy demand forecasting
Econometric model
Input output model
Linear regression
Polynomial fit
title Mathematical modeling of Ethiopia's energy demand by sectors and energy types, with forecasts for the next 30 years
title_full Mathematical modeling of Ethiopia's energy demand by sectors and energy types, with forecasts for the next 30 years
title_fullStr Mathematical modeling of Ethiopia's energy demand by sectors and energy types, with forecasts for the next 30 years
title_full_unstemmed Mathematical modeling of Ethiopia's energy demand by sectors and energy types, with forecasts for the next 30 years
title_short Mathematical modeling of Ethiopia's energy demand by sectors and energy types, with forecasts for the next 30 years
title_sort mathematical modeling of ethiopia s energy demand by sectors and energy types with forecasts for the next 30 years
topic Energy demand forecasting
Econometric model
Input output model
Linear regression
Polynomial fit
url http://www.sciencedirect.com/science/article/pii/S2405844024162160
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