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Effect of stopping hydroelectric power generation on the dynamics of electricity prices: An event study approach

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  • Mosquera-López, Stephanía
  • Uribe, Jorge M.
  • Manotas-Duque, Diego F.

Abstract

Supply shocks in electricity markets that disrupt energy production cause unexpected spikes in prices, which in turn have economic consequences, such as higher risk and therefore higher costs and losses for producers and consumers of electricity. One relevant shock in this sector is the halting of hydroelectric power generation due to the freezing of water reservoirs after the temperature drops below zero degrees Celsius, and therefore less efficient technologies such as thermal plants must begin to produce electricity. Using an event study approach, this shock in the Nord Pool market is explicitly identified, and the economic importance of expanding the interconnected market and the inclusion of more renewable sources in the generation mix of the system to smooth out price spikes is quantified. When a freezing event occurs, it is found that the average electricity prices increase (between €1 and €6), and that the negative relationship between temperature and prices also increases (for each degree that the temperature decreases, prices increase between €1 and €3). However, as expected, these changes are more pronounced in countries that are most dependent on hydropower generation. By identifying this supply shock, relevant insights are presented for market players, such as policy makers, investors, and consumers and producers, whose decisions are influenced by the effect of temperature, particularly when it causes the stopping of hydroelectric plants.

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  • Mosquera-López, Stephanía & Uribe, Jorge M. & Manotas-Duque, Diego F., 2018. "Effect of stopping hydroelectric power generation on the dynamics of electricity prices: An event study approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 94(C), pages 456-467.
  • Handle: RePEc:eee:rensus:v:94:y:2018:i:c:p:456-467
    DOI: 10.1016/j.rser.2018.06.021
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    as
    1. Weron, R & Bierbrauer, M & Trück, S, 2004. "Modeling electricity prices: jump diffusion and regime switching," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 336(1), pages 39-48.
    2. Rafał Weron, 2009. "Heavy-tails and regime-switching in electricity prices," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 69(3), pages 457-473, July.
    3. Mount, Timothy D. & Ning, Yumei & Cai, Xiaobin, 2006. "Predicting price spikes in electricity markets using a regime-switching model with time-varying parameters," Energy Economics, Elsevier, vol. 28(1), pages 62-80, January.
    4. Kevin F. Forbes and Ernest M. Zampelli, 2014. "Do Day-Ahead Electricity Prices Reflect Economic Fundamentals? Evidence from the California ISO," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3).
    5. Hansen, Bruce E, 1999. "Testing for Linearity," Journal of Economic Surveys, Wiley Blackwell, vol. 13(5), pages 551-576, December.
    6. Véliz, Karina D. & Kaufmann, Robert K. & Cleveland, Cutler J. & Stoner, Anne M.K., 2017. "The effect of climate change on electricity expenditures in Massachusetts," Energy Policy, Elsevier, vol. 106(C), pages 1-11.
    7. Keller, Andreas, 2010. "Competition effects of mergers: An event study of the German electricity market," Energy Policy, Elsevier, vol. 38(9), pages 5264-5271, September.
    8. De Jong Cyriel, 2006. "The Nature of Power Spikes: A Regime-Switch Approach," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 10(3), pages 1-28, September.
    9. Haldrup, Niels & Nielsen, Morten Orregaard, 2006. "A regime switching long memory model for electricity prices," Journal of Econometrics, Elsevier, vol. 135(1-2), pages 349-376.
    10. Staffell, Iain & Pfenninger, Stefan, 2018. "The increasing impact of weather on electricity supply and demand," Energy, Elsevier, vol. 145(C), pages 65-78.
    11. Pardo, Angel & Meneu, Vicente & Valor, Enric, 2002. "Temperature and seasonality influences on Spanish electricity load," Energy Economics, Elsevier, vol. 24(1), pages 55-70, January.
    12. Bruce Hansen, 1999. "Testing for Linearity," Journal of Economic Surveys, Wiley Blackwell, vol. 13(5), pages 551-576, December.
    13. Moral-Carcedo, Julián & Pérez-García, Julián, 2015. "Temperature effects on firms’ electricity demand: An analysis of sectorial differences in Spain," Applied Energy, Elsevier, vol. 142(C), pages 407-425.
    14. Bigerna, Simona, 2018. "Estimating temperature effects on the Italian electricity market," Energy Policy, Elsevier, vol. 118(C), pages 257-269.
    15. Fama, Eugene F, et al, 1969. "The Adjustment of Stock Prices to New Information," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 10(1), pages 1-21, February.
    16. Palmquist, Samuel & Bask, Mikael, 2016. "Market dynamics of buyout acquisitions in the renewable energy and cleantech sectors: An event study approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 64(C), pages 271-278.
    17. Hagfors, Lars Ivar & Bunn, Derek & Kristoffersen, Eline & Staver, Tiril Toftdahl & Westgaard, Sjur, 2016. "Modeling the UK electricity price distributions using quantile regression," Energy, Elsevier, vol. 102(C), pages 231-243.
    18. Haldrup Niels & Nielsen Morten Ø., 2006. "Directional Congestion and Regime Switching in a Long Memory Model for Electricity Prices," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 10(3), pages 1-24, September.
    19. Miller, Reid & Golab, Lukasz & Rosenberg, Catherine, 2017. "Modelling weather effects for impact analysis of residential time-of-use electricity pricing," Energy Policy, Elsevier, vol. 105(C), pages 534-546.
    20. Chang, Yoosoon & Kim, Chang Sik & Miller, J. Isaac & Park, Joon Y. & Park, Sungkeun, 2016. "A new approach to modeling the effects of temperature fluctuations on monthly electricity demand," Energy Economics, Elsevier, vol. 60(C), pages 206-216.
    21. Borovkova, Svetlana & Schmeck, Maren Diane, 2017. "Electricity price modeling with stochastic time change," Energy Economics, Elsevier, vol. 63(C), pages 51-65.
    22. Zipp, Alexander, 2017. "The marketability of variable renewable energy in liberalized electricity markets – An empirical analysis," Renewable Energy, Elsevier, vol. 113(C), pages 1111-1121.
    23. Wang, Yaoping & Bielicki, Jeffrey M., 2018. "Acclimation and the response of hourly electricity loads to meteorological variables," Energy, Elsevier, vol. 142(C), pages 473-485.
    24. Potter, Simon M, 1999. "Nonlinear Time Series Modelling: An Introduction," Journal of Economic Surveys, Wiley Blackwell, vol. 13(5), pages 505-528, December.
    25. Pechan, Anna & Eisenack, Klaus, 2014. "The impact of heat waves on electricity spot markets," Energy Economics, Elsevier, vol. 43(C), pages 63-71.
    26. Yoo, Kyungjin & Lee, Youah & Heo, Eunnyeong, 2013. "Economic effects by merger and acquisition types in the renewable energy sector: An event study approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 26(C), pages 694-701.
    27. Mosquera-López, Stephanía & Uribe, Jorge M. & Manotas-Duque, Diego Fernando, 2017. "Nonlinear empirical pricing in electricity markets using fundamental weather factors," Energy, Elsevier, vol. 139(C), pages 594-605.
    28. Nima Amjady & Farshid Keynia, 2011. "A New Neural Network Approach to Short Term Load Forecasting of Electrical Power Systems," Energies, MDPI, vol. 4(3), pages 1-16, March.
    29. Janczura, Joanna & Weron, Rafal, 2010. "An empirical comparison of alternate regime-switching models for electricity spot prices," Energy Economics, Elsevier, vol. 32(5), pages 1059-1073, September.
    30. Kishimoto, Jo & Goto, Mika & Inoue, Kotaro, 2017. "Do acquisitions by electric utility companies create value? Evidence from deregulated markets," Energy Policy, Elsevier, vol. 105(C), pages 212-224.
    31. Sabet, Amir H. & Heaney, Richard, 2016. "An event study analysis of oil and gas firm acreage and reserve acquisitions," Energy Economics, Elsevier, vol. 57(C), pages 215-227.
    32. Kosater, Peter & Mosler, Karl, 2006. "Can Markov regime-switching models improve power-price forecasts? Evidence from German daily power prices," Applied Energy, Elsevier, vol. 83(9), pages 943-958, September.
    33. Jovanović, Saša & Savić, Slobodan & Bojić, Milorad & Djordjević, Zorica & Nikolić, Danijela, 2015. "The impact of the mean daily air temperature change on electricity consumption," Energy, Elsevier, vol. 88(C), pages 604-609.
    34. Simon Potter, 1999. "Nonlinear Time Series Modelling: An Introduction," Journal of Economic Surveys, Wiley Blackwell, vol. 13(5), pages 505-528, December.
    35. Huurman, Christian & Ravazzolo, Francesco & Zhou, Chen, 2012. "The power of weather," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3793-3807.
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