Sustainability · 2018 · 16 citations · 39 references
BusinessEconomicsEnvironmental SciencesEnergy EconomicsEnvironmental ModelingForecastingEconomic AnalysisEconomic ForecastingEnergy Demand ForecastingForecast Error AnalysisTime Series ForecastingTime Series ModelingCarbon Emission AssessmentCarbon Emissions ForecastingDemand Balance ModelingEnergy ConsumptionEnergy Use PredictionMean Absolute ErrorNonlinear Forecasting ModelsSupply-demand Balance
South Africa’s coal consumption accounts for 69.6% of the total energy consumption of South Africa, and this represents more than 88% of African coal consumption, taking the first place in Africa. Thus, predicting the coal demand is necessary, in order to ensure the supply and demand balance of energy, reduce carbon emissions and promote a sustainable development of economy and society. In this study, the linear (Metabolic Grey Model), nonlinear (Non-linear Grey Model), and combined (Metabolic Grey Model-Autoregressive Integrated Moving Average Model) models have been applied to forecast South Africa’s coal consumption for the period of 2017–2030, based on the coal consumption in 2000–2016. The mean absolute percentage errors of the three models are respectively 4.9%, 3.8%, and 3.4%. The forecasting results indicate that the future coal consumption of South Africa appears a downward trend in 2017–2030, dropping by 1.9% per year. Analysis results can provide the data support for the formulation of carbon emission and energy policy.
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Day-ahead wind speed forecasting using f-ARIMA models
Rajesh Kavasseri · Renewable Energy · 2008 · 943 citations