• مطالعات اقتصادی مرتبط با حاملهای انرژی (فسیلی، تجدیدپذیر و برق)
Hossein Hafezi; Mahbube Delfan
Abstract
The electricity industry is not only one of the most significant industries in the nation, but it is also one of the most significant pillars of economic development. The numerous roles that electricity plays in a country's economy make it clear that anticipating electricity consumption is crucial. In ...
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The electricity industry is not only one of the most significant industries in the nation, but it is also one of the most significant pillars of economic development. The numerous roles that electricity plays in a country's economy make it clear that anticipating electricity consumption is crucial. In this regard, the combined ARDL and ARIMA technique is used in the current study to forecast the nation's electricity demand. With an emphasis on the impact of temperature and various rates of economic growth, this study attempts to forecast Iran's total electricity demand over 30 years (2021 to 2050) under 4 alternative scenarios. The development of the scenario is based on the rise in the nation's average temperature and various rates of economic growth. The first and second scenarios rely on the country's average temperature increase of 0. 26% per annum and economic growth rates of 2% and 8%. Furthermore, the third and fourth ones are based on the country's average temperature increase of 0. 45% a year and economic growth rates of 2 and 8%. The study's findings reveal that temperature and economic growth have a substantial impact on how much electricity is consumed, but they also indicate that as temperatures rise and the GDP expands, there will be a huge increase in demand for electricity. Additionally, additional findings show that the power demand is inelastic to price fluctuations. As a result, efforts to reduce electricity consumption should be based on policies to increase energy efficiency as well as policies to regulate temperature and greenhouse gas emissions by increasing the proportion of renewable technologies in the nation's electricity supply portfolio.
Hossein Yadegari; Teymour Mohamadi; Hamid Amadeh; abdorrasoul ghasemi,; hamidreza mostafaee
Abstract
The characteristics of crude oil and the factors affecting the price of this energy carrier have made its price forecast always considered by researchers, oil market participants, governments, and policymakers. Because the price of crude oil is affected by many factors, ongoing studies should be done ...
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The characteristics of crude oil and the factors affecting the price of this energy carrier have made its price forecast always considered by researchers, oil market participants, governments, and policymakers. Because the price of crude oil is affected by many factors, ongoing studies should be done to make more accurate and reliable estimates over time. In this paper, a combination of GM (1,1) and ARIMA models and a hybrid model (GM-ARIMA) for crude oil price forecasting is proposed. The Brent crude oil price data for seasonal (2015Q1-2021Q2), monthly(2020m3-2020m12), and weekly(w12-2020: w16-2021) periods were used to examine this method. The results show that based on the evaluation criteria of mean absolute error percentage (MAPE) and square mean square error (RMSE), the evaluation criteria of MAPE and RMSE in the combined GM-ARIMA model are always lower than the GM and ARIMA models alone. Therefore, the GM-ARIMA hybrid model will be able to predict more accurately than the GM and ARIMA models. Therefore, for more accurate prediction, the GM-ARIMA hybrid model can be used instead of single models.
