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Forecasting the Fuel Consumption and Price for a Future Pandemic Outbreak: A Case Study in the USA under COVID-19

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  • Ahmed Nazmus Sakib

    (School of Aerospace and Mechanical Engineering, University of Oklahoma, Norman, OK 73019, USA)

  • Talayeh Razzaghi

    (School of Industrial and Systems Engineering, University of Oklahoma, Norman, OK 73019, USA)

  • Md Monjur Hossain Bhuiyan

    (School of Aerospace and Mechanical Engineering, University of Oklahoma, Norman, OK 73019, USA)

Abstract

The COVID-19 epidemic and the measures adopted to contain it have had a significant impact on energy patterns throughout the world. The pandemic and movement restrictions led to unpredictable fluctuations in power systems demand and the fuel price for a delayed period. Monkeypox, another viral disease, appeared during the post-COVID period. It is assumed that the outbreak of monkeypox is unlikely due to the implication of preventive measures experienced from COVID-19. At the same time, the probability of an epidemic cannot be blindly overlooked. This paper aims to examine and analyze historical data to look at how much petroleum fuel was used for generating power and how the price of petroleum fuel changed over seven years, from January 2016 to August 2022. This period covers the time before the COVID-19 pandemic, during the pandemic, and after the pandemic. Several time-series forecasting models, including all four benchmark methods (Mean, Naive, Drift, and Snaive), Seasonal and Trend decomposition using Loess (STL), Exponential Smoothing (ETS), and Autoregressive Integrated Moving Average (ARIMA) methods have been applied for both fuel consumption and price prediction. The best forecasting method for fuel price and consumption has been identified among these methods. The best forecasting method for fuel consumption observed is ETS based on the RMSE value, which is 799.59, and the ARIMA method for fuel price, with RMSE 4.67. The paper also utilizes the ARIMAX model by incorporating multiple exogenous variables, such as monthly mean temperature, mean fuel price, and mileage of vehicles traveling during a certain period of pandemic lock-down. It will assist in capturing the non-smooth and stochastic pattern of fuel consumption and price due to the pandemic by separating the seasonal influence and, thus, provide a prediction of the consumption pattern in the event of any future pandemic. The novelty of the article will assist in exploring the potential energy demand in terms of cost and consumption of fuel during any pandemic period, considering the associated abnormalities.

Suggested Citation

  • Ahmed Nazmus Sakib & Talayeh Razzaghi & Md Monjur Hossain Bhuiyan, 2023. "Forecasting the Fuel Consumption and Price for a Future Pandemic Outbreak: A Case Study in the USA under COVID-19," Sustainability, MDPI, vol. 15(17), pages 1-26, August.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:17:p:12692-:d:1222480
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    References listed on IDEAS

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    1. Güngör, Bekir Oray & Ertuğrul, H. Murat & Soytaş, Uğur, 2021. "Impact of Covid-19 outbreak on Turkish gasoline consumption," Technological Forecasting and Social Change, Elsevier, vol. 166(C).
    2. Raydonal Ospina & João A. M. Gondim & Víctor Leiva & Cecilia Castro, 2023. "An Overview of Forecast Analysis with ARIMA Models during the COVID-19 Pandemic: Methodology and Case Study in Brazil," Mathematics, MDPI, vol. 11(14), pages 1-18, July.
    3. Amevi Acakpovi & Alfred Tettey Ternor & Nana Yaw Asabere & Patrick Adjei & Abdul-Shakud Iddrisu, 2020. "Time Series Prediction of Electricity Demand Using Adaptive Neuro-Fuzzy Inference Systems," Mathematical Problems in Engineering, Hindawi, vol. 2020, pages 1-14, August.
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