The impact of COVID-19 pandemic on electricity consumption and electricity demand forecasting accuracy: Empirical evidence from the state of Qatar
<p dir="ltr">The goal of this study is to use machine-learning (ML) techniques and empirical big data to examine the influence of the COVID-19 pandemic on electricity usage and electricity demand forecasting accuracy in buildings in Qatar over time and across sectors. Furthermore, th...
محفوظ في:
| المؤلف الرئيسي: | |
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| مؤلفون آخرون: | , |
| منشور في: |
2022
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| الموضوعات: | |
| الوسوم: |
إضافة وسم
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| _version_ | 1864513561898778624 |
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| author | Ammar Abulibdeh (15785928) |
| author2 | Esmat Zaidan (16855203) Rateb Jabbar (16946565) |
| author2_role | author author |
| author_facet | Ammar Abulibdeh (15785928) Esmat Zaidan (16855203) Rateb Jabbar (16946565) |
| author_role | author |
| dc.creator.none.fl_str_mv | Ammar Abulibdeh (15785928) Esmat Zaidan (16855203) Rateb Jabbar (16946565) |
| dc.date.none.fl_str_mv | 2022-11-01T00:00:00Z |
| dc.identifier.none.fl_str_mv | 10.1016/j.esr.2022.100980 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/journal_contribution/The_impact_of_COVID-19_pandemic_on_electricity_consumption_and_electricity_demand_forecasting_accuracy_Empirical_evidence_from_the_state_of_Qatar/24099567 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Engineering Electrical engineering Information and computing sciences Machine learning COVID-19 Electricity consumption Machine learning Simulation Qatar CPP |
| dc.title.none.fl_str_mv | The impact of COVID-19 pandemic on electricity consumption and electricity demand forecasting accuracy: Empirical evidence from the state of Qatar |
| dc.type.none.fl_str_mv | Text Journal contribution info:eu-repo/semantics/publishedVersion text contribution to journal |
| description | <p dir="ltr">The goal of this study is to use machine-learning (ML) techniques and empirical big data to examine the influence of the COVID-19 pandemic on electricity usage and electricity demand forecasting accuracy in buildings in Qatar over time and across sectors. Furthermore, this study statistically investigates the relationship between building electricity consumption and the number of daily infected cases in the State of Qatar. The effect of the pandemic on electricity usage was quantified during various periods of the pandemic years. Around 1 million electricity meter readings per year were considered for six different types of building usage between the years 2010 and 2021. The findings indicate that there was a gap between the actual and simulated electricity consumption during the pandemic years. Furthermore, the results show that the fluctuation in electricity consumption was correlated with the number of daily infected cases in some socioeconomic sectors. The changes in the pattern of electricity consumption during the pandemic years (2020–2021) affected the accuracy of the ML models in predicting electricity consumption in 2022.</p><h2>Other Information</h2><p dir="ltr">Published in: Energy Strategy Reviews<br>License: <a href="http://creativecommons.org/licenses/by/4.0/" target="_blank">http://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1016/j.esr.2022.100980" target="_blank">https://dx.doi.org/10.1016/j.esr.2022.100980</a></p> |
| eu_rights_str_mv | openAccess |
| id | Manara2_710a8b8de0ded35cf5d48d84b69e526b |
| identifier_str_mv | 10.1016/j.esr.2022.100980 |
| network_acronym_str | Manara2 |
| network_name_str | Manara2 |
| oai_identifier_str | oai:figshare.com:article/24099567 |
| publishDate | 2022 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | The impact of COVID-19 pandemic on electricity consumption and electricity demand forecasting accuracy: Empirical evidence from the state of QatarAmmar Abulibdeh (15785928)Esmat Zaidan (16855203)Rateb Jabbar (16946565)EngineeringElectrical engineeringInformation and computing sciencesMachine learningCOVID-19Electricity consumptionMachine learningSimulationQatarCPP<p dir="ltr">The goal of this study is to use machine-learning (ML) techniques and empirical big data to examine the influence of the COVID-19 pandemic on electricity usage and electricity demand forecasting accuracy in buildings in Qatar over time and across sectors. Furthermore, this study statistically investigates the relationship between building electricity consumption and the number of daily infected cases in the State of Qatar. The effect of the pandemic on electricity usage was quantified during various periods of the pandemic years. Around 1 million electricity meter readings per year were considered for six different types of building usage between the years 2010 and 2021. The findings indicate that there was a gap between the actual and simulated electricity consumption during the pandemic years. Furthermore, the results show that the fluctuation in electricity consumption was correlated with the number of daily infected cases in some socioeconomic sectors. The changes in the pattern of electricity consumption during the pandemic years (2020–2021) affected the accuracy of the ML models in predicting electricity consumption in 2022.</p><h2>Other Information</h2><p dir="ltr">Published in: Energy Strategy Reviews<br>License: <a href="http://creativecommons.org/licenses/by/4.0/" target="_blank">http://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1016/j.esr.2022.100980" target="_blank">https://dx.doi.org/10.1016/j.esr.2022.100980</a></p>2022-11-01T00:00:00ZTextJournal contributioninfo:eu-repo/semantics/publishedVersiontextcontribution to journal10.1016/j.esr.2022.100980https://figshare.com/articles/journal_contribution/The_impact_of_COVID-19_pandemic_on_electricity_consumption_and_electricity_demand_forecasting_accuracy_Empirical_evidence_from_the_state_of_Qatar/24099567CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/240995672022-11-01T00:00:00Z |
| spellingShingle | The impact of COVID-19 pandemic on electricity consumption and electricity demand forecasting accuracy: Empirical evidence from the state of Qatar Ammar Abulibdeh (15785928) Engineering Electrical engineering Information and computing sciences Machine learning COVID-19 Electricity consumption Machine learning Simulation Qatar CPP |
| status_str | publishedVersion |
| title | The impact of COVID-19 pandemic on electricity consumption and electricity demand forecasting accuracy: Empirical evidence from the state of Qatar |
| title_full | The impact of COVID-19 pandemic on electricity consumption and electricity demand forecasting accuracy: Empirical evidence from the state of Qatar |
| title_fullStr | The impact of COVID-19 pandemic on electricity consumption and electricity demand forecasting accuracy: Empirical evidence from the state of Qatar |
| title_full_unstemmed | The impact of COVID-19 pandemic on electricity consumption and electricity demand forecasting accuracy: Empirical evidence from the state of Qatar |
| title_short | The impact of COVID-19 pandemic on electricity consumption and electricity demand forecasting accuracy: Empirical evidence from the state of Qatar |
| title_sort | The impact of COVID-19 pandemic on electricity consumption and electricity demand forecasting accuracy: Empirical evidence from the state of Qatar |
| topic | Engineering Electrical engineering Information and computing sciences Machine learning COVID-19 Electricity consumption Machine learning Simulation Qatar CPP |