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Forecasting Hourly Electricity Demand Under COVID-19 Restrictions

Author

Listed:
  • Ali K k

    (Industrial Engineering Department, Kadir Has University, Istanbul, Turkey.)

  • Erg n Y kseltan

    (Industrial Engineering Department, Kadir Has University, Istanbul, Turkey.)

  • Mustafa Hekimo lu

    (Industrial Engineering Department, Kadir Has University, Istanbul, Turkey.)

  • Esra Agca Aktunc

    (Industrial Engineering Department, Kadir Has University, Istanbul, Turkey.)

  • Ahmet Y cekaya

    (Industrial Engineering Department, Kadir Has University, Istanbul, Turkey.)

  • Ay e Bilge

    (Industrial Engineering Department, Kadir Has University, Istanbul, Turkey.)

Abstract

The rapid spread of the COVID-19 pandemic has severely impacted many sectors including the electricity sector. The restrictions such as lockdowns, remote-working, and -schooling significantly altered the consumers behaviors and demand structure especially due to a large number of people working at home. Accurate demand forecasts and detailed production plans are crucial for cost-efficient generation and transmission of electricity. In this research, the restrictions and their corresponding timing are classified and mapped with the Turkish electricity demand data to analyze the impact of the restrictions on total demand using a multiple linear regression model. In addition, the model is utilized to forecast the electricity demand in pandemic conditions and to analyze how different types of restrictions impact the total electricity demand. It is found that among three levels of COVID-19 restrictions, age-specific restrictions and the complete lockdown have different effects on the electricity demand on weekends and weekdays. In general, new scheduling approaches for daily and weekly loads are required to avoid supply-demand mismatches as COVID-19 significantly changed the consumer behavior, which appears as altered daily and weekly load profiles of the country. Long-term policy implications for the energy transition and lessons learned from the COVID-19 experience are also discussed.

Suggested Citation

  • Ali K k & Erg n Y kseltan & Mustafa Hekimo lu & Esra Agca Aktunc & Ahmet Y cekaya & Ay e Bilge, 2022. "Forecasting Hourly Electricity Demand Under COVID-19 Restrictions," International Journal of Energy Economics and Policy, Econjournals, vol. 12(1), pages 73-85.
    • Handle: RePEc:eco:journ2:2022-01-10
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    References listed on IDEAS

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    More about this item

    Keywords

    COVID-19; Pandemic; Electricity Demand; Daily Demand Curve; Restrictions; Regression;
    All these keywords.

    JEL classification:

    • Q47 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy Forecasting
    • E17 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Forecasting and Simulation: Models and Applications
    • Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - General

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