2019
DOI: 10.1108/gs-05-2019-0012
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Forecasting the total energy consumption in Ghana using grey models

Abstract: Purpose The purpose of this paper is to forecast the future trend of Ghana’s total energy consumption (GTEC) using two grey models, which are GM(1,1) and the grey Verhulst model. Design/methodology/approach The paper employs the use of Even model GM(1,1) and the grey Verhulst model to forecast GTEC for the next five years. Since various models were used, the margin for error is minimal, hence resulting in a better choice for forecasting the future. The forecast reveals that the GTEC for the next five years w… Show more

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Cited by 11 publications
(3 citation statements)
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References 26 publications
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“…Since its establishment, many scholars have studied and applied grey prediction models in different branches of academia. The model has been successfully applied for the prediction of power system load (Morita et al, 1995), total GS 11,3 energy consumption in Ghana (Katani, 2019), asphalt pavement performance (Tang and Xiao, 2019), and the Chinese tourism indicators (Javed et al, 2020a), among others. The model Even GM (1,1) is defined in the following part.…”
Section: Basic Knowledge 21 Grey Forecasting Theorymentioning
confidence: 99%
“…Since its establishment, many scholars have studied and applied grey prediction models in different branches of academia. The model has been successfully applied for the prediction of power system load (Morita et al, 1995), total GS 11,3 energy consumption in Ghana (Katani, 2019), asphalt pavement performance (Tang and Xiao, 2019), and the Chinese tourism indicators (Javed et al, 2020a), among others. The model Even GM (1,1) is defined in the following part.…”
Section: Basic Knowledge 21 Grey Forecasting Theorymentioning
confidence: 99%
“…However, most of the previous studies developed on energy focused more on renewable resources, predicting energy consumption and in particular, overall energy production (Dind etal., 2018;Katani, 2019;Kaur & Ahuja, 2017;Sarkodie, 2017;Wu et al, 2017). Some too focused on factors affecting hydropower generation (Kabo-bah et al, 2016;Michieka et al, 2021).…”
Section: Introductionmentioning
confidence: 99%
“…[ 42 ] established a hybrid model that can forecast changes of capital intensity, to forecast the capital intensity of new energy industry in China. By using the mean GM(1,1) and grey Verhulst model, Katani [ 43 ] forecast the total energy consumption in Ghana. Instead of the least squares method for parameter estimation in the traditional GM(1,1) model, Moonchai & Chutsagulprom [ 44 ] used Kalman filtering to estimate parameters of the model.…”
Section: Introductionmentioning
confidence: 99%