IDEAS home Printed from https://ideas.repec.org/h/spr/isochp/978-1-4419-9586-5_13.html
   My bibliography  Save this book chapter

Stochastic Equilibrium Models for Generation Capacity Expansion

In: Stochastic Optimization Methods in Finance and Energy

Author

Listed:
  • Andreas Ehrenmann

    (GDF SUEZ)

  • Yves Smeers

    (Université catholique de Louvain)

Abstract

Capacity expansion models in the power sector were among the first applications of operations research to the industry. The models lost some of their appeal at the inception of restructuring even though they still offer a lot of possibilities and are in many respect irreplaceable provided they are adapted to the new environment. We introduce stochastic equilibrium versions of these models that we believe provide a relevant context for looking at the current very risky market where the power industry invests and operates. We then take up different questions raised by the new environment. Some are due to developments of the industry like demand side management: an optimization framework has difficulties accommodating them but the more general equilibrium paradigm offers additional possibilities. We then look at the insertion of risk-related investment practices that developed with the new environment and may not be easy to accommodate in an optimization context. Specifically we consider the use of plant-specific discount rates that we derive by including stochastic discount rates in the equilibrium model. Linear discount factors only price systematic risk. We therefore complete the discussion by inserting different risk functions (for different agents) in order to account for additional unpriced idiosyncratic risk in investments. These different models can be cast in a single mathematical representation but they do not have the same mathematical properties. We illustrate the impact of these phenomena on a small but realistic example.

Suggested Citation

  • Andreas Ehrenmann & Yves Smeers, 2011. "Stochastic Equilibrium Models for Generation Capacity Expansion," International Series in Operations Research & Management Science, in: Marida Bertocchi & Giorgio Consigli & Michael A. H. Dempster (ed.), Stochastic Optimization Methods in Finance and Energy, edition 1, chapter 0, pages 273-310, Springer.
  • Handle: RePEc:spr:isochp:978-1-4419-9586-5_13
    DOI: 10.1007/978-1-4419-9586-5_13
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Citations

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


    Cited by:

    1. Munoz, Francisco D. & van der Weijde, Adriaan Hendrik & Hobbs, Benjamin F. & Watson, Jean-Paul, 2017. "Does risk aversion affect transmission and generation planning? A Western North America case study," Energy Economics, Elsevier, vol. 64(C), pages 213-225.
    2. Gauthier Maere d’Aertrycke & Alexander Shapiro & Yves Smeers, 2013. "Risk exposure and Lagrange multipliers of nonanticipativity constraints in multistage stochastic problems," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 77(3), pages 393-405, June.
    3. Mohseni, Soheil & Brent, Alan C. & Kelly, Scott & Browne, Will N., 2022. "Demand response-integrated investment and operational planning of renewable and sustainable energy systems considering forecast uncertainties: A systematic review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 158(C).
    4. Ambrosius, Mirjam & Egerer, Jonas & Grimm, Veronika & van der Weijde, Adriaan H., 2022. "Risk aversion in multilevel electricity market models with different congestion pricing regimes," Energy Economics, Elsevier, vol. 105(C).
    5. P'ia Amigo & Sebasti'an Cea-Echenique & Felipe Feijoo, 2020. "An Emissions Trading System to reach NDC targets in the Chilean electric sector," Papers 2005.03843, arXiv.org.
    6. Acevedo, Giancarlo & Bernales, Alejandro & Flores, Andrés & Inzunza, Andrés & Moreno, Rodrigo, 2021. "The effect of environmental policies on risk reductions in energy generation," Journal of Economic Dynamics and Control, Elsevier, vol. 126(C).
    7. Maria Teresa Vespucci & Marida Bertocchi & Laureano F. Escudero & Stefano Zigrino, 2013. "A risk averse stochastic optimization model for power generation capacity expansion," Working Papers (2013-) 1305_qum, University of Bergamo, Department of Management, Economics and Quantitative Methods.
    8. de Maere d’Aertrycke, Gauthier & Ehrenmann, Andreas & Smeers, Yves, 2017. "Investment with incomplete markets for risk: The need for long-term contracts," Energy Policy, Elsevier, vol. 105(C), pages 571-583.

    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:spr:isochp:978-1-4419-9586-5_13. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.