IDEAS home Printed from https://ideas.repec.org/a/eee/jbfina/v97y2018icp1-19.html
   My bibliography  Save this article

Managing renewable energy production risk

Author

Listed:
  • Hain, Martin
  • Schermeyer, Hans
  • Uhrig-Homburg, Marliese
  • Fichtner, Wolf

Abstract

The growing share of renewables paired with their intermittent nature introduces significant new challenges for market participants along the value-chain in power markets. Taking the view of an owner of such a physical renewable asset we showcase the management of the associated stochastic production risks in Germany, one of the most dynamic electricity markets and the largest producer of renewable energy in the EU-28. We find that unhedged renewable portfolios are very risky and existing vanilla derivatives are poor hedges. New exotic quantity-related weather contracts proposed by major energy exchanges (EEX) show a lot of potential but are still very illiquid. Their hedging performance is heavily driven by the market wide renewable generation portfolio which, in its current state, favors specific regions. In the long-run price-related derivatives will transform into more useful hedging instruments due to the growing importance of renewables in the formation of wholesale market prices.

Suggested Citation

  • Hain, Martin & Schermeyer, Hans & Uhrig-Homburg, Marliese & Fichtner, Wolf, 2018. "Managing renewable energy production risk," Journal of Banking & Finance, Elsevier, vol. 97(C), pages 1-19.
  • Handle: RePEc:eee:jbfina:v:97:y:2018:i:c:p:1-19
    DOI: 10.1016/j.jbankfin.2018.09.001
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378426618301882
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.jbankfin.2018.09.001?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    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. Markus Burger & Bernhard Klar & Alfred Muller & Gero Schindlmayr, 2004. "A spot market model for pricing derivatives in electricity markets," Quantitative Finance, Taylor & Francis Journals, vol. 4(1), pages 109-122.
    2. Cludius, Johanna & Hermann, Hauke & Matthes, Felix Chr. & Graichen, Verena, 2014. "The merit order effect of wind and photovoltaic electricity generation in Germany 2008–2016: Estimation and distributional implications," Energy Economics, Elsevier, vol. 44(C), pages 302-313.
    3. Caporin, Massimiliano & Preś, Juliusz, 2012. "Modelling and forecasting wind speed intensity for weather risk management," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3459-3476.
    4. Helyette Geman & A. Roncoroni, 2006. "Understanding the Fine Structure of Electricity Prices," Post-Print halshs-00144198, HAL.
    5. Joshua D. Woodard & Philip Garcia, 2008. "Basis risk and weather hedging effectiveness," Agricultural Finance Review, Emerald Group Publishing Limited, vol. 68(1), pages 99-117, May.
    6. 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.
    7. Keles, Dogan & Genoese, Massimo & Möst, Dominik & Ortlieb, Sebastian & Fichtner, Wolf, 2013. "A combined modeling approach for wind power feed-in and electricity spot prices," Energy Policy, Elsevier, vol. 59(C), pages 213-225.
    8. Alvaro Cartea & Marcelo Figueroa, 2005. "Pricing in Electricity Markets: A Mean Reverting Jump Diffusion Model with Seasonality," Applied Mathematical Finance, Taylor & Francis Journals, vol. 12(4), pages 313-335.
    9. Füss, Roland & Mahringer, Steffen & Prokopczuk, Marcel, 2015. "Electricity derivatives pricing with forward-looking information," Journal of Economic Dynamics and Control, Elsevier, vol. 58(C), pages 34-57.
    10. Ziel, Florian & Steinert, Rick, 2016. "Electricity price forecasting using sale and purchase curves: The X-Model," Energy Economics, Elsevier, vol. 59(C), pages 435-454.
    11. Ben Hambly & Sam Howison & Tino Kluge, 2009. "Modelling spikes and pricing swing options in electricity markets," Quantitative Finance, Taylor & Francis Journals, vol. 9(8), pages 937-949.
    12. Shawn Cole & Xavier Giné & James Vickery, 2017. "How Does Risk Management Influence Production Decisions? Evidence from a Field Experiment," Review of Financial Studies, Society for Financial Studies, vol. 30(6), pages 1935-1970.
    13. Ivana Štulec, 2017. "Effectiveness of Weather Derivatives as a Risk Management Tool in Food Retail: The Case of Croatia," IJFS, MDPI, vol. 5(1), pages 1-15, January.
    14. Alvaro Cartea & Marcelo Figueroa & Helyette Geman, 2009. "Modelling Electricity Prices with Forward Looking Capacity Constraints," Applied Mathematical Finance, Taylor & Francis Journals, vol. 16(2), pages 103-122.
    15. Grothe, Oliver & Schnieders, Julius, 2011. "Spatial Dependence in Wind and Optimal Wind Power Allocation: A Copula Based Analysis," EWI Working Papers 2011-5, Energiewirtschaftliches Institut an der Universitaet zu Koeln (EWI).
    16. Cornaggia, Jess, 2013. "Does risk management matter? Evidence from the U.S. agricultural industry," Journal of Financial Economics, Elsevier, vol. 109(2), pages 419-440.
    17. Grothe, Oliver & Schnieders, Julius, 2011. "Spatial dependence in wind and optimal wind power allocation: A copula-based analysis," Energy Policy, Elsevier, vol. 39(9), pages 4742-4754, September.
    18. Florian Ziel & Rick Steinert, 2015. "Electricity Price Forecasting using Sale and Purchase Curves: The X-Model," Papers 1509.00372, arXiv.org, revised Aug 2016.
    19. Francisco Pérez-González & Hayong Yun, 2013. "Risk Management and Firm Value: Evidence from Weather Derivatives," Journal of Finance, American Finance Association, vol. 68(5), pages 2143-2176, October.
    20. Andreas Wagner, 2014. "Residual Demand Modeling and Application to Electricity Pricing," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2).
    21. repec:dau:papers:123456789/11500 is not listed on IDEAS
    22. Hain, Martin & Schermeyer, Hans & Uhrig-Homburg, Marliese & Fichtner, Wolf, 2017. "An Electricity Price Modeling Framework for Renewable-Dominant Markets," Working Paper Series in Production and Energy 23, Karlsruhe Institute of Technology (KIT), Institute for Industrial Production (IIP).
    23. Ederington, Louis H. & Salas, Jesus M., 2008. "Minimum variance hedging when spot price changes are partially predictable," Journal of Banking & Finance, Elsevier, vol. 32(5), pages 654-663, May.
    24. Jan Seifert & Marliese Uhrig-Homburg, 2007. "Modelling jumps in electricity prices: theory and empirical evidence," Review of Derivatives Research, Springer, vol. 10(1), pages 59-85, January.
    25. G. David Haushalter, 2000. "Financing Policy, Basis Risk, and Corporate Hedging: Evidence from Oil and Gas Producers," Journal of Finance, American Finance Association, vol. 55(1), pages 107-152, February.
    26. Gregory W. Brown & Klaus Bjerre Toft, 2002. "How Firms Should Hedge," Review of Financial Studies, Society for Financial Studies, vol. 15(4), pages 1283-1324.
    27. repec:dau:papers:123456789/1433 is not listed on IDEAS
    28. Hélyette Geman & Andrea Roncoroni, 2006. "Understanding the Fine Structure of Electricity Prices," The Journal of Business, University of Chicago Press, vol. 79(3), pages 1225-1262, May.
    29. Figlewski, Stephen, 1984. "Hedging Performance and Basis Risk in Stock Index Futures," Journal of Finance, American Finance Association, vol. 39(3), pages 657-669, July.
    30. A. Alexandridis & A. Zapranis, 2013. "Wind Derivatives: Modeling and Pricing," Computational Economics, Springer;Society for Computational Economics, vol. 41(3), pages 299-326, March.
    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. Finnah, Benedikt & Gönsch, Jochen & Ziel, Florian, 2022. "Integrated day-ahead and intraday self-schedule bidding for energy storage systems using approximate dynamic programming," European Journal of Operational Research, Elsevier, vol. 301(2), pages 726-746.
    2. Lado-Sestayo, Rubén & De Llano-Paz, Fernando & Vivel-Búa, Milagros & Martínez-Salgueiro, Andrea, 2023. "Commodity exposure in the eurozone: How EU energy security is conditioned by the Euro," Energy, Elsevier, vol. 277(C).
    3. Andoni, Merlinda & Robu, Valentin & Flynn, David & Abram, Simone & Geach, Dale & Jenkins, David & McCallum, Peter & Peacock, Andrew, 2019. "Blockchain technology in the energy sector: A systematic review of challenges and opportunities," Renewable and Sustainable Energy Reviews, Elsevier, vol. 100(C), pages 143-174.
    4. Johannes Kaufmann & Philipp Artur Kienscherf & Wolfgang Ketter, 2020. "Modeling and Managing Joint Price and Volumetric Risk for Volatile Electricity Portfolios," Energies, MDPI, vol. 13(14), pages 1-19, July.
    5. Shahnazi, Rouhollah & Alimohammadlou, Moslem, 2022. "Investigating risks in renewable energy in oil-producing countries through multi-criteria decision-making methods based on interval type-2 fuzzy sets: A case study of Iran," Renewable Energy, Elsevier, vol. 191(C), pages 1009-1027.
    6. Wang, Wei & Cova, Gregorio & Zio, Enrico, 2022. "A clustering-based framework for searching vulnerabilities in the operation dynamics of Cyber-Physical Energy Systems," Reliability Engineering and System Safety, Elsevier, vol. 222(C).
    7. Taghizadeh-Hesary, Farhad & Yoshino, Naoyuki, 2019. "The way to induce private participation in green finance and investment," Finance Research Letters, Elsevier, vol. 31(C), pages 98-103.
    8. Mosquera-López, Stephania & Uribe, Jorge M., 2022. "Pricing the risk due to weather conditions in small variable renewable energy projects," Applied Energy, Elsevier, vol. 322(C).
    9. Gambacorta, Leonardo & Pancotto, Livia & Reghezza, Alessio & Spaggiari, Martina, 2022. "Gender diversity in bank boardrooms and green lending: Evidence from euro area credit register data," CEPR Discussion Papers 17650, C.E.P.R. Discussion Papers.
    10. Russo, Marianna & Kraft, Emil & Bertsch, Valentin & Keles, Dogan, 2022. "Short-term risk management of electricity retailers under rising shares of decentralized solar generation," Energy Economics, Elsevier, vol. 109(C).
    11. Carrillo-Nieves, Danay & Rostro Alanís, Magdalena J. & de la Cruz Quiroz, Reynaldo & Ruiz, Héctor A. & Iqbal, Hafiz M.N. & Parra-Saldívar, Roberto, 2019. "Current status and future trends of bioethanol production from agro-industrial wastes in Mexico," Renewable and Sustainable Energy Reviews, Elsevier, vol. 102(C), pages 63-74.

    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. Hain, Martin & Schermeyer, Hans & Uhrig-Homburg, Marliese & Fichtner, Wolf, 2017. "An Electricity Price Modeling Framework for Renewable-Dominant Markets," Working Paper Series in Production and Energy 23, Karlsruhe Institute of Technology (KIT), Institute for Industrial Production (IIP).
    2. Hain, Martin & Kargus, Tobias & Schermeyer, Hans & Uhrig-Homburg, Marliese & Fichtner, Wolf, 2022. "An electricity price modeling framework for renewable-dominant markets," Working Paper Series in Production and Energy 66, Karlsruhe Institute of Technology (KIT), Institute for Industrial Production (IIP).
    3. Deschatre, Thomas & Féron, Olivier & Gruet, Pierre, 2021. "A survey of electricity spot and futures price models for risk management applications," Energy Economics, Elsevier, vol. 102(C).
    4. Umut Ugurlu & Ilkay Oksuz & Oktay Tas, 2018. "Electricity Price Forecasting Using Recurrent Neural Networks," Energies, MDPI, vol. 11(5), pages 1-23, May.
    5. 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.
    6. Coulon, Michael & Powell, Warren B. & Sircar, Ronnie, 2013. "A model for hedging load and price risk in the Texas electricity market," Energy Economics, Elsevier, vol. 40(C), pages 976-988.
    7. Thomas Deschatre & Olivier F'eron & Pierre Gruet, 2021. "A survey of electricity spot and futures price models for risk management applications," Papers 2103.16918, arXiv.org, revised Jul 2021.
    8. Nowotarski, Jakub & Tomczyk, Jakub & Weron, Rafał, 2013. "Robust estimation and forecasting of the long-term seasonal component of electricity spot prices," Energy Economics, Elsevier, vol. 39(C), pages 13-27.
    9. Fanone, Enzo & Gamba, Andrea & Prokopczuk, Marcel, 2013. "The case of negative day-ahead electricity prices," Energy Economics, Elsevier, vol. 35(C), pages 22-34.
    10. Janczura, Joanna & Trück, Stefan & Weron, Rafał & Wolff, Rodney C., 2013. "Identifying spikes and seasonal components in electricity spot price data: A guide to robust modeling," Energy Economics, Elsevier, vol. 38(C), pages 96-110.
    11. Mayer, Klaus & Trück, Stefan, 2018. "Electricity markets around the world," Journal of Commodity Markets, Elsevier, vol. 9(C), pages 77-100.
    12. Hinderks, W.J. & Wagner, A., 2020. "Factor models in the German electricity market: Stylized facts, seasonality, and calibration," Energy Economics, Elsevier, vol. 85(C).
    13. Rafal Weron & Florian Ziel, 2018. "Electricity price forecasting," HSC Research Reports HSC/18/08, Hugo Steinhaus Center, Wroclaw University of Technology.
    14. Mwampashi, Muthe Mathias & Nikitopoulos, Christina Sklibosios & Konstandatos, Otto & Rai, Alan, 2021. "Wind generation and the dynamics of electricity prices in Australia," Energy Economics, Elsevier, vol. 103(C).
    15. Smith, Michael Stanley & Shively, Thomas S., 2018. "Econometric modeling of regional electricity spot prices in the Australian market," Energy Economics, Elsevier, vol. 74(C), pages 886-903.
    16. Timothy Christensen & Stan Hurn & Kenneth Lindsay, 2009. "It Never Rains but it Pours: Modeling the Persistence of Spikes in Electricity Prices," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1), pages 25-48.
    17. Jan Seifert & Marliese Uhrig-Homburg, 2007. "Modelling jumps in electricity prices: theory and empirical evidence," Review of Derivatives Research, Springer, vol. 10(1), pages 59-85, January.
    18. Wagner, Andreas & Ramentol, Enislay & Schirra, Florian & Michaeli, Hendrik, 2022. "Short- and long-term forecasting of electricity prices using embedding of calendar information in neural networks," Journal of Commodity Markets, Elsevier, vol. 28(C).
    19. Hinderks, W.J. & Wagner, A., 2019. "Pricing German Energiewende products: Intraday cap/floor futures," Energy Economics, Elsevier, vol. 81(C), pages 287-296.
    20. Nadja Klein & Michael Stanley Smith & David J. Nott, 2020. "Deep Distributional Time Series Models and the Probabilistic Forecasting of Intraday Electricity Prices," Papers 2010.01844, arXiv.org, revised May 2021.

    More about this item

    Keywords

    Power markets; Risk management; Structural model; Hedging; Weather-risks; Climate change economics;
    All these keywords.

    JEL classification:

    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
    • Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - General
    • Q42 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Alternative Energy Sources

    Statistics

    Access and download statistics

    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:jbfina:v:97:y:2018:i:c:p:1-19. 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/jbf .

    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.