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Effects of the COVID-19 Pandemic on the Spot Price of Colombian Electricity

Author

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  • Andrés Oviedo-Gómez

    (School of Electrical and Electronic Engineering, Universidad del Valle, 76001 Cali, Colombia)

  • Sandra Milena Londoño-Hernández

    (School of Electrical and Electronic Engineering, Universidad del Valle, 76001 Cali, Colombia)

  • Diego Fernando Manotas-Duque

    (School of Industrial Engineering, Universidad del Valle, 76001 Cali, Colombia)

Abstract

COVID-19 disease shocked global economic activity and affected the electricity markets due to lockdown and work-from-home policies. Therefore, this study proposes an empirical analysis to identify the electricity spot price response during the preventive and mandatory insulation in Colombia, where the economic contraction caused the largest decrease in the electricity demand, especially in the industrial sector. The methodology applied was quantile regression to quantify the non-linear effect on the spot price returns, and two sample periods were selected to contrast the results: 2018 and 2019. The main findings showed that regulated demand variation caused the highest variability on the spot price dynamic during the strict quarantine. However, the price could not fully capture the effects of the demand change due to the short duration of the shock and, also, the price variability in 2019 was higher than 2020 by an El Niño shock.

Suggested Citation

  • Andrés Oviedo-Gómez & Sandra Milena Londoño-Hernández & Diego Fernando Manotas-Duque, 2021. "Effects of the COVID-19 Pandemic on the Spot Price of Colombian Electricity," Energies, MDPI, vol. 14(21), pages 1-14, October.
  • Handle: RePEc:gam:jeners:v:14:y:2021:i:21:p:6989-:d:664220
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    References listed on IDEAS

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    1. Editorial, 2020. "Covid-19 and Climate Change," Journal, Review of Agrarian Studies, vol. 10(1), pages 5-6, January-J.
    2. López Prol, Javier & O, Sungmin, 2020. "Impact of COVID-19 measures on electricity consumption," MPRA Paper 101649, University Library of Munich, Germany.
    3. Rafal Weron & Florian Ziel, 2018. "Electricity price forecasting," HSC Research Reports HSC/18/08, Hugo Steinhaus Center, Wroclaw University of Science and Technology.
    4. Bierbrauer, Michael & Menn, Christian & Rachev, Svetlozar T. & Truck, Stefan, 2007. "Spot and derivative pricing in the EEX power market," Journal of Banking & Finance, Elsevier, vol. 31(11), pages 3462-3485, November.
    5. Weron, Rafal & Przybyłowicz, Beata, 2000. "Hurst analysis of electricity price dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 283(3), pages 462-468.
    6. Aviad Navon & Ram Machlev & David Carmon & Abiodun Emmanuel Onile & Juri Belikov & Yoash Levron, 2021. "Effects of the COVID-19 Pandemic on Energy Systems and Electric Power Grids—A Review of the Challenges Ahead," Energies, MDPI, vol. 14(4), pages 1-14, February.
    7. Ketterer, Janina C., 2014. "The impact of wind power generation on the electricity price in Germany," Energy Economics, Elsevier, vol. 44(C), pages 270-280.
    8. Hinderks, W.J. & Wagner, A., 2020. "Factor models in the German electricity market: Stylized facts, seasonality, and calibration," Energy Economics, Elsevier, vol. 85(C).
    9. Nowotarski, Jakub & Weron, Rafał, 2018. "Recent advances in electricity price forecasting: A review of probabilistic forecasting," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 1548-1568.
    10. Sana Mujeeb & Nadeem Javaid & Manzoor Ilahi & Zahid Wadud & Farruh Ishmanov & Muhammad Khalil Afzal, 2019. "Deep Long Short-Term Memory: A New Price and Load Forecasting Scheme for Big Data in Smart Cities," Sustainability, MDPI, vol. 11(4), pages 1-29, February.
    11. Weron, Rafał, 2014. "Electricity price forecasting: A review of the state-of-the-art with a look into the future," International Journal of Forecasting, Elsevier, vol. 30(4), pages 1030-1081.
    12. Jiang, Peng & Fan, Yee Van & Klemeš, Jiří Jaromír, 2021. "Impacts of COVID-19 on energy demand and consumption: Challenges, lessons and emerging opportunities," Applied Energy, Elsevier, vol. 285(C).
    13. Karakatsani, Nektaria V. & Bunn, Derek W., 2008. "Forecasting electricity prices: The impact of fundamentals and time-varying coefficients," International Journal of Forecasting, Elsevier, vol. 24(4), pages 764-785.
    14. Huisman, Ronald & Mahieu, Ronald, 2003. "Regime jumps in electricity prices," Energy Economics, Elsevier, vol. 25(5), pages 425-434, September.
    15. Emilio Ghiani & Marco Galici & Mario Mureddu & Fabrizio Pilo, 2020. "Impact on Electricity Consumption and Market Pricing of Energy and Ancillary Services during Pandemic of COVID-19 in Italy," Energies, MDPI, vol. 13(13), pages 1-19, July.
    16. Santiago, I. & Moreno-Munoz, A. & Quintero-Jiménez, P. & Garcia-Torres, F. & Gonzalez-Redondo, M.J., 2021. "Electricity demand during pandemic times: The case of the COVID-19 in Spain," Energy Policy, Elsevier, vol. 148(PA).
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    1. Andr s Oviedo-G mez & Sandra Milena Londo o-Hern ndez & Diego Fernando Manotas-Duque, 2023. "Directional Spillover of Fossil Fuels Prices on a Hydrothermal Power Generation Market," International Journal of Energy Economics and Policy, Econjournals, vol. 13(1), pages 85-90, January.

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