IDEAS home Printed from
   My bibliography  Save this article

Insuring wind energy production


  • D’Amico, Guglielmo
  • Petroni, Filippo
  • Prattico, Flavio


This paper presents an insurance contract that the supplier of wind energy may subscribe in order to immunize the production of electricity against the volatility of the wind speed process. The other party of the contract may be any dispatchable energy producer, like gas turbine or hydroelectric generator, which can supply the required energy in case of little or no wind. The adoption of a stochastic wind speed model allows the computation of the fair premium that the wind power supplier has to pay in order to hedge the risk of inadequate output of electricity at any time. Recursive type equations are obtained for the prospective mathematical reserves of the insurance contract and for their higher order moments. The model and the validity of the results are illustrated through a numerical example.

Suggested Citation

  • D’Amico, Guglielmo & Petroni, Filippo & Prattico, Flavio, 2017. "Insuring wind energy production," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 467(C), pages 542-553.
  • Handle: RePEc:eee:phsmap:v:467:y:2017:i:c:p:542-553
    DOI: 10.1016/j.physa.2016.10.023

    Download full text from publisher

    File URL:
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

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

    References listed on IDEAS

    1. Janssen, J. & de Dominicis, R., 1984. "Finite non-homogeneous semi-Markov processes: Theoretical and computational aspects," Insurance: Mathematics and Economics, Elsevier, vol. 3(3), pages 157-165, July.
    2. D’Amico, Guglielmo & Petroni, Filippo & Prattico, Flavio, 2015. "Economic performance indicators of wind energy based on wind speed stochastic modeling," Applied Energy, Elsevier, vol. 154(C), pages 290-297.
    3. Guglielmo D'Amico & Filippo Petroni, 2012. "Weighted-indexed semi-Markov models for modeling financial returns," Papers 1205.2551,, revised Jun 2012.
    4. Beenstock, Michael, 1995. "The stochastic economics of windpower," Energy Economics, Elsevier, vol. 17(1), pages 27-37, January.
    5. Maegebier, Alexander, 2013. "Valuation and risk assessment of disability insurance using a discrete time trivariate Markov renewal reward process," Insurance: Mathematics and Economics, Elsevier, vol. 53(3), pages 802-811.
    6. Nfaoui, H. & Essiarab, H. & Sayigh, A.A.M., 2004. "A stochastic Markov chain model for simulating wind speed time series at Tangiers, Morocco," Renewable Energy, Elsevier, vol. 29(8), pages 1407-1418.
    7. Guglielmo D'Amico & Filippo Petroni, 2011. "A semi-Markov model with memory for price changes," Papers 1109.4259,, revised Dec 2011.
    8. Ettoumi, F.Youcef & Sauvageot, H & Adane, A.-E.-H, 2003. "Statistical bivariate modelling of wind using first-order Markov chain and Weibull distribution," Renewable Energy, Elsevier, vol. 28(11), pages 1787-1802.
    9. repec:eee:reensy:v:144:y:2015:i:c:p:170-177 is not listed on IDEAS
    10. Kantz, Holger & Holstein, Detlef & Ragwitz, Mario & K. Vitanov, Nikolay, 2004. "Markov chain model for turbulent wind speed data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 342(1), pages 315-321.
    11. Milbrodt, Hartmut, 1999. "Hattendorff's theorem for non-smooth continuous-time Markov models I: Theory," Insurance: Mathematics and Economics, Elsevier, vol. 25(2), pages 181-195, November.
    12. Guglielmo D'Amico & Filippo Petroni & Flavio Prattico, 2013. "Wind speed modeled as an indexed semi‐Markov process," Environmetrics, John Wiley & Sons, Ltd., vol. 24(6), pages 367-376, September.
    13. Ji, Min & Hardy, Mary & Li, Johnny Siu-Hang, 2012. "A Semi-Markov Multiple State Model for Reverse Mortgage Terminations," Annals of Actuarial Science, Cambridge University Press, vol. 6(02), pages 235-257, September.
    14. D’Amico, Guglielmo & Petroni, Filippo & Prattico, Flavio, 2014. "Wind speed and energy forecasting at different time scales: A nonparametric approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 406(C), pages 59-66.
    15. D'Amico, Guglielmo & Guillen, Montserrat & Manca, Raimondo, 2009. "Full backward non-homogeneous semi-Markov processes for disability insurance models: A Catalunya real data application," Insurance: Mathematics and Economics, Elsevier, vol. 45(2), pages 173-179, October.
    Full references (including those not matched with items on IDEAS)


    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:phsmap:v:467:y:2017:i:c:p:542-553. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Dana Niculescu). General contact details of provider: .

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.