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

被引:12
作者
Mosquera-Lopez, Stephania [1 ]
Uribe, Jorge M. [2 ,3 ]
Manotas-Duque, Diego F. [1 ]
机构
[1] Univ Valle, Sch Ind Engn, Calle 13 100-00, Cali, Colombia
[2] Univ Barcelona, Riskctr, Av Diagonal 690, Barcelona 08034, Spain
[3] Univ Valle, Dept Econ, Calle 13 100-00, Cali, Colombia
关键词
Electricity prices; Hydropower; Weather; Event study; Threshold regression; REGIME-SWITCHING MODELS; RENEWABLE ENERGY; WEATHER; TEMPERATURE; IMPACT; MARKETS; ACQUISITIONS;
D O I
10.1016/j.rser.2018.06.021
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
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 (SIC)1 and (SIC)6), and that the negative relationship between temperature and prices also increases (for each degree that the temperature decreases, prices increase between (SIC)1 and (SIC)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.
引用
收藏
页码:456 / 467
页数:12
相关论文
共 47 条
  • [1] A New Neural Network Approach to Short Term Load Forecasting of Electrical Power Systems
    Amjady, Nima
    Keynia, Farshid
    [J]. ENERGIES, 2011, 4 (03) : 488 - 503
  • [2] Bierbrauer M, 2004, LECT NOTES COMPUT SC, V3039, P859
  • [3] Estimating temperature effects on the Italian electricity market
    Bigerna, Simona
    [J]. ENERGY POLICY, 2018, 118 : 257 - 269
  • [4] Electricity price modeling with stochastic time change
    Borovkova, Svetlana
    Schmeck, Maren Diane
    [J]. ENERGY ECONOMICS, 2017, 63 : 51 - 65
  • [5] Analysis and Forecasting of Electricity Price Risks with Quantile Factor Models
    Bunn, Derek
    Andresen, Arne
    Chen, Dipeng
    Westgaard, Sjur
    [J]. ENERGY JOURNAL, 2016, 37 (01) : 101 - 122
  • [6] A new approach to modeling the effects of temperature fluctuations on monthly electricity demand
    Chang, Yoosoon
    Kim, Chang Sik
    Miller, J. Isaac
    Park, Joon Y.
    Park, Sungkeun
    [J]. ENERGY ECONOMICS, 2016, 60 : 206 - 216
  • [7] Electricity Price Forecasting With Extreme Learning Machine and Bootstrapping
    Chen, Xia
    Dong, Zhao Yang
    Meng, Ke
    Ku, Yan
    Wong, Kit Po
    Ngan, H. W.
    [J]. IEEE TRANSACTIONS ON POWER SYSTEMS, 2012, 27 (04) : 2055 - 2062
  • [8] Forecasting electricity price volatility with the Markov-switching GARCH model: Evidence from the Nordic electric power market
    Cifter, Atilla
    [J]. ELECTRIC POWER SYSTEMS RESEARCH, 2013, 102 : 61 - 67
  • [9] Cochrane JH, 2005, ASSET PRICING, P1
  • [10] De Jong C, 2006, STUD NONLINEAR DYN E, V10