Forecasting the Fuel Consumption and Price for a Future Pandemic Outbreak: A Case Study in the USA under COVID-19
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 disea...
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description | 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. |
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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.</description><identifier>ISSN: 2071-1050</identifier><identifier>EISSN: 2071-1050</identifier><identifier>DOI: 10.3390/su151712692</identifier><language>eng</language><publisher>Basel: MDPI AG</publisher><subject>Case studies ; Coronaviruses ; COVID-19 ; Economic conditions ; Energy consumption ; Energy industry ; Epidemics ; Force and energy ; Forecasting ; Fossil fuels ; Gasoline prices ; Influence ; Investigations ; Laws, regulations and rules ; Pandemics ; Sustainability ; Time series ; Variables</subject><ispartof>Sustainability, 2023-08, Vol.15 (17), p.12692</ispartof><rights>COPYRIGHT 2023 MDPI AG</rights><rights>2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). 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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.</description><subject>Case studies</subject><subject>Coronaviruses</subject><subject>COVID-19</subject><subject>Economic conditions</subject><subject>Energy consumption</subject><subject>Energy industry</subject><subject>Epidemics</subject><subject>Force and energy</subject><subject>Forecasting</subject><subject>Fossil fuels</subject><subject>Gasoline prices</subject><subject>Influence</subject><subject>Investigations</subject><subject>Laws, regulations and rules</subject><subject>Pandemics</subject><subject>Sustainability</subject><subject>Time series</subject><subject>Variables</subject><issn>2071-1050</issn><issn>2071-1050</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><recordid>eNptkU1LAzEQhhdRUNSTfyDgSWRrJtlNGm9ltVoQKla9hjSbrdF2U_MB-u-NH6AFZw4zvDwzw8wUxRHgAaUCn4UENXAgTJCtYo9gDiXgGm__yXeLwxCecTZKQQDbK17HzhutQrT9AsUng8bJLFHj-pBW62hdj1TfoltvtUGd80hlICZv0G3WzcpqNE1x7o16OUcj1Khg0Cym9h3Z_qvdw2yEUiY9aqaPk4sSxEGx06llMIc_cb94GF_eN9flzfRq0oxuSk1rHkvKhao7BUTN6wqL1gwFh4rmTSpQ8yGHuaAAFcNYMdp2wLTSrW7rjhJos0D3i-PvvmvvXpMJUT675Ps8UpIhI5ywmohfaqGWRtq-c9ErvbJByxFnVcVqTkmmBv9Q2b9O4HrT2axvFJxsFGQmmre4UCkEOZndbbKn36z2LgRvOrn2dqX8uwQsPz8r_3yWfgC0vZC5</recordid><startdate>20230801</startdate><enddate>20230801</enddate><creator>Sakib, Ahmed Nazmus</creator><creator>Razzaghi, Talayeh</creator><creator>Bhuiyan, Md Monjur Hossain</creator><general>MDPI AG</general><scope>AAYXX</scope><scope>CITATION</scope><scope>ISR</scope><scope>4U-</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><orcidid>https://orcid.org/0009-0008-6651-1889</orcidid></search><sort><creationdate>20230801</creationdate><title>Forecasting the Fuel Consumption and Price for a Future Pandemic Outbreak: A Case Study in the USA under COVID-19</title><author>Sakib, Ahmed Nazmus ; Razzaghi, Talayeh ; Bhuiyan, Md Monjur Hossain</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c357t-379a5fa12ab5409de89714307141ab871b93114600a63df16cacdcd5f321d3df3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Case studies</topic><topic>Coronaviruses</topic><topic>COVID-19</topic><topic>Economic conditions</topic><topic>Energy consumption</topic><topic>Energy industry</topic><topic>Epidemics</topic><topic>Force and energy</topic><topic>Forecasting</topic><topic>Fossil fuels</topic><topic>Gasoline prices</topic><topic>Influence</topic><topic>Investigations</topic><topic>Laws, regulations and rules</topic><topic>Pandemics</topic><topic>Sustainability</topic><topic>Time series</topic><topic>Variables</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Sakib, Ahmed Nazmus</creatorcontrib><creatorcontrib>Razzaghi, Talayeh</creatorcontrib><creatorcontrib>Bhuiyan, Md Monjur Hossain</creatorcontrib><collection>CrossRef</collection><collection>Gale In Context: Science</collection><collection>University Readers</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Access via ProQuest (Open Access)</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><jtitle>Sustainability</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Sakib, Ahmed Nazmus</au><au>Razzaghi, Talayeh</au><au>Bhuiyan, Md Monjur Hossain</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Forecasting the Fuel Consumption and Price for a Future Pandemic Outbreak: A Case Study in the USA under COVID-19</atitle><jtitle>Sustainability</jtitle><date>2023-08-01</date><risdate>2023</risdate><volume>15</volume><issue>17</issue><spage>12692</spage><pages>12692-</pages><issn>2071-1050</issn><eissn>2071-1050</eissn><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.</abstract><cop>Basel</cop><pub>MDPI AG</pub><doi>10.3390/su151712692</doi><orcidid>https://orcid.org/0009-0008-6651-1889</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Case studies Coronaviruses COVID-19 Economic conditions Energy consumption Energy industry Epidemics Force and energy Forecasting Fossil fuels Gasoline prices Influence Investigations Laws, regulations and rules Pandemics Sustainability Time series Variables |
title | Forecasting the Fuel Consumption and Price for a Future Pandemic Outbreak: A Case Study in the USA under COVID-19 |
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