IDEAS home Printed from https://ideas.repec.org/p/cam/camdae/1647.html
   My bibliography  Save this paper

Does risk aversion affect transmission and generation planning? A Western North America case study

Author

Listed:
  • Munoz, F. D.
  • van der Weijde, A. H.
  • Hobbs, B. F.
  • Watson, J-P.

Abstract

We investigate the effects of risk aversion on optimal transmission and generation expansion planning in a competitive and complete market. To do so, we formulate a stochastic model that minimizes a weighted average of expected transmission and generation costs and their conditional value at risk (CVaR). We show that the solution of this optimization problem is equivalent to the solution of a perfectly competitive risk-averse Stackelberg equilibrium, in which a risk-averse transmission planner maximizes welfare after which risk-averse generators maximize profits. This model is then applied to a 240-bus representation of the Western Electricity Coordinating Council, in which we examine the impact of risk aversion on levels and spatial patterns of generation and transmission investment. Although the impact of risk aversion remains small at an aggregate level, state-level impacts on generation and transmission investment can be significant, which emphasizes the importance of explicit consideration of risk aversion in planning models.

Suggested Citation

  • Munoz, F. D. & van der Weijde, A. H. & Hobbs, B. F. & Watson, J-P., 2016. "Does risk aversion affect transmission and generation planning? A Western North America case study," Cambridge Working Papers in Economics 1647, Faculty of Economics, University of Cambridge.
  • Handle: RePEc:cam:camdae:1647
    as

    Download full text from publisher

    File URL: http://www.econ.cam.ac.uk/research-files/repec/cam/pdf/cwpe1647.pdf
    Download Restriction: no

    References listed on IDEAS

    as
    1. van der Weijde, Adriaan Hendrik & Hobbs, Benjamin F., 2012. "The economics of planning electricity transmission to accommodate renewables: Using two-stage optimisation to evaluate flexibility and the cost of disregarding uncertainty," Energy Economics, Elsevier, vol. 34(6), pages 2089-2101.
    2. Huang, Yun-Hsun & Wu, Jung-Hua, 2008. "A portfolio risk analysis on electricity supply planning," Energy Policy, Elsevier, vol. 36(2), pages 627-641, February.
    3. Fuss, Sabine & Szolgayova, Jana & Obersteiner, Michael & Gusti, Mykola, 2008. "Investment under market and climate policy uncertainty," Applied Energy, Elsevier, pages 708-721.
    4. Fabien Roques & Céline Hiroux & Marcelo Saguan, 2009. "Optimal Wind Power Deployment in Europe - a Portfolio Approach," RSCAS Working Papers 2009/17, European University Institute.
    5. Deng, S.J. & Oren, S.S., 2006. "Electricity derivatives and risk management," Energy, Elsevier, vol. 31(6), pages 940-953.
    6. Janne Kettunen, Derek W. Bunn and William Blyth & Derek W. Bunn & William Blyth, 2011. "Investment Propensities under Carbon Policy Uncertainty," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1), pages 77-118.
    7. Meunier, Guy, 2013. "Risk aversion and technology mix in an electricity market," Energy Economics, Elsevier, pages 866-874.
    8. 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.
    9. Fan, Lin & Hobbs, Benjamin F. & Norman, Catherine S., 2010. "Risk aversion and CO2 regulatory uncertainty in power generation investment: Policy and modeling implications," Journal of Environmental Economics and Management, Elsevier, vol. 60(3), pages 193-208, November.
    10. Hugonnier, Julien & Morellec, Erwan, 2007. "Corporate control and real investment in incomplete markets," Journal of Economic Dynamics and Control, Elsevier, vol. 31(5), pages 1781-1800, May.
    11. Kamalinia, Saeed & Shahidehpour, Mohammad & Wu, Lei, 2014. "Sustainable resource planning in energy markets," Applied Energy, Elsevier, pages 112-120.
    12. L. Eeckhoudt & C. Gollier & H. Schlesinger, 2005. "Economic and financial decisions under risk," Post-Print hal-00325882, HAL.
    13. Barradale, Merrill Jones, 2010. "Impact of public policy uncertainty on renewable energy investment: Wind power and the production tax credit," Energy Policy, Elsevier, vol. 38(12), pages 7698-7709, December.
    14. 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.
    15. Ruiz, C. & Conejo, A.J., 2015. "Robust transmission expansion planning," European Journal of Operational Research, Elsevier, vol. 242(2), pages 390-401.
    16. Francisco Munoz & Enzo Sauma & Benjamin Hobbs, 2013. "Approximations in power transmission planning: implications for the cost and performance of renewable portfolio standards," Journal of Regulatory Economics, Springer, vol. 43(3), pages 305-338, June.
    17. Enzo Sauma & Shmuel Oren, 2006. "Proactive planning and valuation of transmission investments in restructured electricity markets," Journal of Regulatory Economics, Springer, vol. 30(3), pages 358-387, November.
    18. Willems, Bert & Morbee, Joris, 2010. "Market completeness: How options affect hedging and investments in the electricity sector," Energy Economics, Elsevier, vol. 32(4), pages 786-795, July.
    19. Enzo Sauma & Shmuel Oren, 2006. "Proactive planning and valuation of transmission investments in restructured electricity markets," Journal of Regulatory Economics, Springer, vol. 30(3), pages 261-290, November.
    20. Hu, Ming-Che & Hobbs, Benjamin F., 2010. "Analysis of multi-pollutant policies for the U.S. power sector under technology and policy uncertainty using MARKAL," Energy, Elsevier, vol. 35(12), pages 5430-5442.
    21. Pozo, David & Contreras, Javier & Sauma, Enzo, 2013. "If you build it, he will come: Anticipative power transmission planning," Energy Economics, Elsevier, vol. 36(C), pages 135-146.
    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. repec:eee:eneeco:v:64:y:2017:i:c:p:131-148 is not listed on IDEAS
    2. repec:eee:eneeco:v:64:y:2017:i:c:p:55-62 is not listed on IDEAS

    More about this item

    Keywords

    risk aversion; stochastic programming; transmission planning; generation planning;

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • D80 - Microeconomics - - Information, Knowledge, and Uncertainty - - - General
    • L94 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Electric Utilities
    • Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - General

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:cam:camdae:1647. 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: (Jake Dyer). General contact details of provider: http://www.econ.cam.ac.uk/ .

    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.