IDEAS home Printed from https://ideas.repec.org/a/eee/eneeco/v32y2010i6p1268-1276.html
   My bibliography  Save this article

Insuring unit failures in electricity markets

Author

Listed:
  • Pineda, S.
  • Conejo, A.J.
  • Carrión, M.

Abstract

An electric energy producer participates in futures markets in the hope of hedging the risk of trading in the pool. However, this producer is required to supply the energy associated with all its signed forward contracts even if some of its units are forced out due to unexpected failures. In this case, the producer must purchase some of the energy needed to meet its futures market commitments in the pool, which may result in high losses if the pool prices happen to be higher than the forward contract prices. To mitigate these losses, the producer can take out insurance against the forced outages of its units. Using a stochastic programming model, this paper analyzes the convenience of signing an insurance against unit failure by an electric energy producer and its impact on forward contracting decisions. Results from a realistic case study are provided and analyzed.

Suggested Citation

  • Pineda, S. & Conejo, A.J. & Carrión, M., 2010. "Insuring unit failures in electricity markets," Energy Economics, Elsevier, vol. 32(6), pages 1268-1276, November.
  • Handle: RePEc:eee:eneeco:v:32:y:2010:i:6:p:1268-1276
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0140-9883(10)00029-0
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Huisman, Ronald & Mahieu, Ronald & Schlichter, Felix, 2009. "Electricity portfolio management: Optimal peak/off-peak allocations," Energy Economics, Elsevier, vol. 31(1), pages 169-174, January.
    2. F J Nogales & A J Conejo, 2006. "Electricity price forecasting through transfer function models," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 57(4), pages 350-356, April.
    3. Conejo, Antonio J. & Contreras, Javier & Espinola, Rosa & Plazas, Miguel A., 2005. "Forecasting electricity prices for a day-ahead pool-based electric energy market," International Journal of Forecasting, Elsevier, vol. 21(3), pages 435-462.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Álvaro Lorca & X. Andy Sun & Eugene Litvinov & Tongxin Zheng, 2016. "Multistage Adaptive Robust Optimization for the Unit Commitment Problem," Operations Research, INFORMS, vol. 64(1), pages 32-51, February.
    2. Fernandes, Gláucia & Gomes, Leonardo & Vasconcelos, Gabriel & Brandão, Luiz, 2016. "Mitigating wind exposure with zero-cost collar insurance," Renewable Energy, Elsevier, vol. 99(C), pages 336-346.
    3. Xiaojia Guo & Alexandros Beskos & Afzal Siddiqui, 2016. "The natural hedge of a gas-fired power plant," Computational Management Science, Springer, vol. 13(1), pages 63-86, January.
    4. Dorea Chin & Afzal Siddiqui, 2014. "Capacity expansion and forward contracting in a duopolistic power sector," Computational Management Science, Springer, vol. 11(1), pages 57-86, January.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Weron, Rafal & Misiorek, Adam, 2008. "Forecasting spot electricity prices: A comparison of parametric and semiparametric time series models," International Journal of Forecasting, Elsevier, vol. 24(4), pages 744-763.
    2. Jakub Nowotarski & Rafał Weron, 2015. "Computing electricity spot price prediction intervals using quantile regression and forecast averaging," Computational Statistics, Springer, vol. 30(3), pages 791-803, September.
    3. Alonso Fernández, Andrés Modesto & García-Martos, Carolina & Rodríguez, Julio & Sánchez, María Jesús, 2008. "Seasonal dynamic factor analysis and bootstrap inference : application to electricity market forecasting," DES - Working Papers. Statistics and Econometrics. WS ws081406, Universidad Carlos III de Madrid. Departamento de Estadística.
    4. Xiaojia Guo & Alexandros Beskos & Afzal Siddiqui, 2016. "The natural hedge of a gas-fired power plant," Computational Management Science, Springer, vol. 13(1), pages 63-86, January.
    5. Tan, Zhongfu & Zhang, Jinliang & Wang, Jianhui & Xu, Jun, 2010. "Day-ahead electricity price forecasting using wavelet transform combined with ARIMA and GARCH models," Applied Energy, Elsevier, vol. 87(11), pages 3606-3610, November.
    6. 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.
    7. Jónsson, Tryggvi & Pinson, Pierre & Madsen, Henrik, 2010. "On the market impact of wind energy forecasts," Energy Economics, Elsevier, vol. 32(2), pages 313-320, March.
    8. Diongue, Abdou Kâ & Guégan, Dominique & Vignal, Bertrand, 2009. "Forecasting electricity spot market prices with a k-factor GIGARCH process," Applied Energy, Elsevier, vol. 86(4), pages 505-510, April.
    9. Mara Madaleno & Carlos Pinho, 2010. "Hedging Performance and Multiscale Relationships in the German Electricity Spot and Futures Markets," JRFM, MDPI, vol. 3(1), pages 1-37, December.
    10. Billé, Anna Gloria & Gianfreda, Angelica & Del Grosso, Filippo & Ravazzolo, Francesco, 2023. "Forecasting electricity prices with expert, linear, and nonlinear models," International Journal of Forecasting, Elsevier, vol. 39(2), pages 570-586.
    11. Weron, Rafał & Zator, Michał, 2015. "A note on using the Hodrick–Prescott filter in electricity markets," Energy Economics, Elsevier, vol. 48(C), pages 1-6.
    12. Chen, Yenming J. & Sheu, Jiuh-Biing & Lirn, Taih-Cherng, 2012. "Fault tolerance modeling for an e-waste recycling supply chain," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 48(5), pages 897-906.
    13. 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.
    14. Àlex Alonso & Jordi de la Hoz & Helena Martín & Sergio Coronas & Pep Salas & José Matas, 2020. "A Comprehensive Model for the Design of a Microgrid under Regulatory Constraints Using Synthetical Data Generation and Stochastic Optimization," Energies, MDPI, vol. 13(21), pages 1-26, October.
    15. Galarneau-Vincent, Rémi & Gauthier, Geneviève & Godin, Frédéric, 2023. "Foreseeing the worst: Forecasting electricity DART spikes," Energy Economics, Elsevier, vol. 119(C).
    16. Bowden, Nicholas & Payne, James E., 2008. "Short term forecasting of electricity prices for MISO hubs: Evidence from ARIMA-EGARCH models," Energy Economics, Elsevier, vol. 30(6), pages 3186-3197, November.
    17. Salas-Molina, Francisco & Martin, Francisco J. & Rodríguez-Aguilar, Juan A. & Serrà, Joan & Arcos, Josep Ll., 2017. "Empowering cash managers to achieve cost savings by improving predictive accuracy," International Journal of Forecasting, Elsevier, vol. 33(2), pages 403-415.
    18. Ama Agyeiwaa Abrokwah, 2018. "Price and Volatility Spillovers in the Electricity Reliability Council of Texas Day-Ahead Electricity Market," International Journal of Energy Economics and Policy, Econjournals, vol. 8(6), pages 322-330.
    19. Daniel Manfre Jaimes & Manuel Zamudio López & Hamidreza Zareipour & Mike Quashie, 2023. "A Hybrid Model for Multi-Day-Ahead Electricity Price Forecasting considering Price Spikes," Forecasting, MDPI, vol. 5(3), pages 1-23, July.
    20. Gianfreda, Angelica & Ravazzolo, Francesco & Rossini, Luca, 2020. "Comparing the forecasting performances of linear models for electricity prices with high RES penetration," International Journal of Forecasting, Elsevier, vol. 36(3), pages 974-986.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:eneeco:v:32:y:2010:i:6:p:1268-1276. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eneco .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.