IDEAS home Printed from https://ideas.repec.org/a/eee/eneeco/v40y2013icp598-608.html

Risk–return incentives in liberalised electricity markets

Author

Listed:
  • Lynch, Muireann Á.
  • Shortt, Aonghus
  • Tol, Richard S.J.
  • O'Malley, Mark J.

Abstract

We employ Monte Carlo analysis to determine the distribution of returns for various electricity generation technologies. Costs and revenues for each technology are calculated by means of a unit commitment and economic dispatch algorithm at hourly resolution. This represents a considerable contribution to the literature as costs and revenues are determined endogenously, which in turn allows the returns of midmerit and peaking plant to be examined. Market entry is determined on the basis of a heuristic while market exit is according to a predetermined retirement schedule. The results show that CCGT is the investment technology of choice for baseload-only portfolios, while OCGT proves optimal when all technologies are considered. The high capital costs of baseload generation reduce incentives to invest. The methodology can be expanded to consider random outages, revenues from scarcity prices, capacity markets and ancillary service payments.

Suggested Citation

  • Lynch, Muireann Á. & Shortt, Aonghus & Tol, Richard S.J. & O'Malley, Mark J., 2013. "Risk–return incentives in liberalised electricity markets," Energy Economics, Elsevier, vol. 40(C), pages 598-608.
    • Handle: RePEc:eee:eneeco:v:40:y:2013:i:c:p:598-608
    DOI: 10.1016/j.eneco.2013.08.015
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0140988313001886
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.eneco.2013.08.015?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 look for a different version below or

    for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Awerbuch, Shimon, 2000. "Investing in photovoltaics: risk, accounting and the value of new technology," Energy Policy, Elsevier, vol. 28(14), pages 1023-1035, November.
    2. Bar-Lev, Dan & Katz, Steven, 1976. "A Portfolio Approach to Fossil Fuel Procurement in the Electric Utility Industry," Journal of Finance, American Finance Association, vol. 31(3), pages 933-947, June.
    3. Harry Markowitz, 1952. "Portfolio Selection," Journal of Finance, American Finance Association, vol. 7(1), pages 77-91, March.
    4. Roques, Fabien & Hiroux, Céline & Saguan, Marcelo, 2010. "Optimal wind power deployment in Europe--A portfolio approach," Energy Policy, Elsevier, vol. 38(7), pages 3245-3256, July.
    5. repec:aen:journl:1998v19-03-a06 is not listed on IDEAS
    6. Rafal Weron, 2006. "Modeling and Forecasting Electricity Loads and Prices: A Statistical Approach," HSC Books, Hugo Steinhaus Center, Wroclaw University of Science and Technology, number hsbook0601, December.
    7. Delarue, Erik & De Jonghe, Cedric & Belmans, Ronnie & D'haeseleer, William, 2011. "Applying portfolio theory to the electricity sector: Energy versus power," Energy Economics, Elsevier, vol. 33(1), pages 12-23, January.
    8. Troy, Niamh & Denny, Eleanor & O'Malley, Mark, 2010. "Base-load cycling on a system with significant wind penetration," MPRA Paper 34848, University Library of Munich, Germany.
    9. Roques, Fabien A. & Newbery, David M. & Nuttall, William J., 2008. "Fuel mix diversification incentives in liberalized electricity markets: A Mean-Variance Portfolio theory approach," Energy Economics, Elsevier, vol. 30(4), pages 1831-1849, July.
    10. Twomey, Paul & Neuhoff, Karsten, 2010. "Wind power and market power in competitive markets," Energy Policy, Elsevier, vol. 38(7), pages 3198-3210, July.
    11. Hobbs, Benjamin F., 1995. "Optimization methods for electric utility resource planning," European Journal of Operational Research, Elsevier, vol. 83(1), pages 1-20, May.
    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. Paulino Martinez-Fernandez & Fernando deLlano-Paz & Anxo Calvo-Silvosa & Isabel Soares, 2019. "Assessing Renewable Energy Sources for Electricity (RES-E) Potential Using a CAPM-Analogous Multi-Stage Model," Energies, MDPI, vol. 12(19), pages 1-20, September.
    2. Hao Chen & Chi Kong Chyong & Jia-Ning Kang & Yi-Ming Wei, 2018. "Economic dispatch in the electricity sector in China: potential benefits and challenges ahead," Working Papers EPRG 1819, Energy Policy Research Group, Cambridge Judge Business School, University of Cambridge.
    3. Lynch & John Curtis, 2016. "The effects of wind generation capacity on electricity prices and generation costs: a Monte Carlo analysis," Applied Economics, Taylor & Francis Journals, vol. 48(2), pages 133-151, January.
    4. Lynch, Muireann & Devine, Mel & Bertsch, Valentin, 2018. "The role of power-to-gas in the future energy system: how much is needed and who wants to invest?," Papers WP590, Economic and Social Research Institute (ESRI).
    5. Paulino Martinez-Fernandez & Fernando deLlano-Paz & Anxo Calvo-Silvosa & Isabel Soares, 2018. "Pollutant versus non-pollutant generation technologies: a CML-analogous analysis," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 20(1), pages 199-212, December.
    6. Jano-Ito, Marco A. & Crawford-Brown, Douglas, 2017. "Investment decisions considering economic, environmental and social factors: An actors' perspective for the electricity sector of Mexico," Energy, Elsevier, vol. 121(C), pages 92-106.
    7. Zeng, Ximei & Zhou, Zhongbao & Gong, Yeming & Liu, Wenbin, 2022. "A data envelopment analysis model integrated with portfolio theory for energy mix adjustment: Evidence in the power industry," Socio-Economic Planning Sciences, Elsevier, vol. 83(C).
    8. Janko, Samantha A. & Johnson, Nathan G., 2018. "Scalable multi-agent microgrid negotiations for a transactive energy market," Applied Energy, Elsevier, vol. 229(C), pages 715-727.
    9. Curtis, John & Lynch, Muireann Á. & Zubiate, Laura, 2016. "The impact of the North Atlantic Oscillation on electricity markets: A case study on Ireland," Energy Economics, Elsevier, vol. 58(C), pages 186-198.
    10. Muireann Á. Lynch & Richard Tol & Mark J. O’Malley, 2014. "Minimising costs and variability of electricity generation by means of optimal electricity interconnection utilisation," Working Paper Series 6814, Department of Economics, University of Sussex Business School.
    11. deLlano-Paz, Fernando & Calvo-Silvosa, Anxo & Antelo, Susana Iglesias & Soares, Isabel, 2017. "Energy planning and modern portfolio theory: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 636-651.
    12. Koltsaklis, Nikolaos E. & Dagoumas, Athanasios S., 2018. "State-of-the-art generation expansion planning: A review," Applied Energy, Elsevier, vol. 230(C), pages 563-589.
    13. Russo, Marianna & Bertsch, Valentin, 2020. "A looming revolution: Implications of self-generation for the risk exposure of retailers," Energy Economics, Elsevier, vol. 92(C).
    14. Lynch, Muireann & Devine, Mel T. & Bertsch, Valentin, 2019. "The role of power-to-gas in the future energy system: Market and portfolio effects," Energy, Elsevier, vol. 185(C), pages 1197-1209.
    15. Curtis, John & Lynch, Muireann Á. & Zubiate, Laura, 2016. "Carbon dioxide (CO2) emissions from electricity: The influence of the North Atlantic Oscillation," Applied Energy, Elsevier, vol. 161(C), pages 487-496.
    16. Tietjen, Oliver & Pahle, Michael & Fuss, Sabine, 2016. "Investment risks in power generation: A comparison of fossil fuel and renewable energy dominated markets," Energy Economics, Elsevier, vol. 58(C), pages 174-185.
    17. Wei, Yi-Ming & Chen, Hao & Chyong, Chi Kong & Kang, Jia-Ning & Liao, Hua & Tang, Bao-Jun, 2018. "Economic dispatch savings in the coal-fired power sector: An empirical study of China," Energy Economics, Elsevier, vol. 74(C), pages 330-342.

    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. Pérez Odeh, Rodrigo & Watts, David & Flores, Yarela, 2018. "Planning in a changing environment: Applications of portfolio optimisation to deal with risk in the electricity sector," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 3808-3823.
    2. Jano-Ito, Marco A. & Crawford-Brown, Douglas, 2017. "Investment decisions considering economic, environmental and social factors: An actors' perspective for the electricity sector of Mexico," Energy, Elsevier, vol. 121(C), pages 92-106.
    3. Tietjen, Oliver & Pahle, Michael & Fuss, Sabine, 2016. "Investment risks in power generation: A comparison of fossil fuel and renewable energy dominated markets," Energy Economics, Elsevier, vol. 58(C), pages 174-185.
    4. Sinsel, Simon R. & Yan, Xuqian & Stephan, Annegret, 2019. "Building resilient renewable power generation portfolios: The impact of diversification on investors’ risk and return," Applied Energy, Elsevier, vol. 254(C).
    5. Marrero, Gustavo A. & Puch, Luis A. & Ramos-Real, Francisco J., 2015. "Mean-variance portfolio methods for energy policy risk management," International Review of Economics & Finance, Elsevier, vol. 40(C), pages 246-264.
    6. Vithayasrichareon, Peerapat & MacGill, Iain F., 2013. "Assessing the value of wind generation in future carbon constrained electricity industries," Energy Policy, Elsevier, vol. 53(C), pages 400-412.
    7. Allan, Grant & Eromenko, Igor & McGregor, Peter & Swales, Kim, 2011. "The regional electricity generation mix in Scotland: A portfolio selection approach incorporating marine technologies," Energy Policy, Elsevier, vol. 39(1), pages 6-22, January.
    8. Frank A. Wolak, 2016. "Level versus Variability Trade-offs in Wind and Solar Generation Investments: The Case of California," NBER Working Papers 22494, National Bureau of Economic Research, Inc.
    9. de-Llano Paz, Fernando & Antelo, Susana Iglesias & Calvo Silvosa, Anxo & Soares, Isabel, 2014. "The technological and environmental efficiency of the EU-27 power mix: An evaluation based on MPT," Energy, Elsevier, vol. 69(C), pages 67-81.
    10. deLlano-Paz, Fernando & Calvo-Silvosa, Anxo & Iglesias Antelo, Susana & Soares, Isabel, 2015. "The European low-carbon mix for 2030: The role of renewable energy sources in an environmentally and socially efficient approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 48(C), pages 49-61.
    11. Roques, Fabien & Hiroux, Céline & Saguan, Marcelo, 2010. "Optimal wind power deployment in Europe--A portfolio approach," Energy Policy, Elsevier, vol. 38(7), pages 3245-3256, July.
    12. Lynch & John Curtis, 2016. "The effects of wind generation capacity on electricity prices and generation costs: a Monte Carlo analysis," Applied Economics, Taylor & Francis Journals, vol. 48(2), pages 133-151, January.
    13. Fridgen, Gilbert & Halbrügge, Stephanie & Olenberger, Christian & Weibelzahl, Martin, 2020. "The insurance effect of renewable distributed energy resources against uncertain electricity price developments," Energy Economics, Elsevier, vol. 91(C).
    14. Dornan, Matthew & Jotzo, Frank, 2015. "Renewable technologies and risk mitigation in small island developing states: Fiji’s electricity sector," Renewable and Sustainable Energy Reviews, Elsevier, vol. 48(C), pages 35-48.
    15. Li, Carmen & Chyong, Chi Kong & Reiner, David M. & Roques, Fabien, 2024. "Taking a Portfolio approach to wind and solar deployment: The case of the National Electricity Market in Australia," Applied Energy, Elsevier, vol. 369(C).
    16. Zhang, Shuang & Zhao, Tao & Xie, Bai-Chen, 2018. "What is the optimal power generation mix of China? An empirical analysis using portfolio theory," Applied Energy, Elsevier, vol. 229(C), pages 522-536.
    17. Inzunza, Andrés & Moreno, Rodrigo & Bernales, Alejandro & Rudnick, Hugh, 2016. "CVaR constrained planning of renewable generation with consideration of system inertial response, reserve services and demand participation," Energy Economics, Elsevier, vol. 59(C), pages 104-117.
    18. Locatelli, Giorgio & Mancini, Mauro, 2011. "Large and small baseload power plants: Drivers to define the optimal portfolios," Energy Policy, Elsevier, vol. 39(12), pages 7762-7775.
    19. Su, Qing & Zhou, Peng & Ding, Hao, 2025. "Portfolio optimization of diversified energy transition investments with multiple risks," Renewable and Sustainable Energy Reviews, Elsevier, vol. 219(C).
    20. Leroux, Anke D. & Martin, Vance L. & Zheng, Hao, 2018. "Addressing water shortages by force of habit," Resource and Energy Economics, Elsevier, vol. 53(C), pages 42-61.

    More about this item

    Keywords

    ;
    ;
    ;

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • L94 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Electric Utilities

    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:eneeco:v:40:y:2013:i:c:p:598-608. 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.