IDEAS home Printed from https://ideas.repec.org/a/ers/journl/vxvy2012i4p31-46.html

The Impact of Fuel and CO2 Prices on Electricity Power Plans

Author

Listed:
  • Paula Fereira
  • Isabel Soares
  • Madalena Araujo

Abstract

The increasing uncertainty surrounding the electricity generating sector has implications on the forecasting accuracy and makes sensitivity analysis an essential tool for electricity power planning. The fuel price volatility and the emissions trading schemes represent major sources of uncertainty, as the relative economic interest of thermo power plants and of renewable energy sources largely depends on these two factors. In this paper, an electricity planning model will be used to analyse both these aspects, identifying the relative importance and sensitiveness of the optimal electricity power plans to changes on these parameters.

Suggested Citation

  • Paula Fereira & Isabel Soares & Madalena Araujo, 2012. "The Impact of Fuel and CO2 Prices on Electricity Power Plans," European Research Studies Journal, European Research Studies Journal, vol. 0(4), pages 31-46.
    • Handle: RePEc:ers:journl:v:xv:y:2012:i:4:p:31-46
    as

    Download full text from publisher

    File URL: http://www.ersj.eu/repec/ers/papers/12_4_p2.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. repec:aen:journl:2005v26-02-a03 is not listed on IDEAS
    2. 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)

    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. M. Jenabi & S. M. T. Fatemi Ghomi & S. A. Torabi & Moeen Sammak Jalali, 2022. "An accelerated Benders decomposition algorithm for stochastic power system expansion planning using sample average approximation," OPSEARCH, Springer;Operational Research Society of India, vol. 59(4), pages 1304-1336, December.
    2. Berna Tektas Sivrikaya & Ferhan Cebi & Hasan Hüseyin Turan & Nihat Kasap & Dursun Delen, 2017. "A fuzzy long-term investment planning model for a GenCo in a hybrid electricity market considering climate change impacts," Information Systems Frontiers, Springer, vol. 19(5), pages 975-991, October.
    3. C. K. Woo & K. H. Cao & H. Qi & J. Zarnikau & R. Li, 2024. "Price responsiveness of solar and wind capacity demands," Post-Print hal-04597188, HAL.
    4. Reza Nadimi & Masahito Takahashi & Koji Tokimatsu & Mika Goto, 2024. "The Reliability and Profitability of Virtual Power Plant with Short-Term Power Market Trading and Non-Spinning Reserve Diesel Generator," Energies, MDPI, vol. 17(9), pages 1-19, April.
    5. De Jonghe, C. & Hobbs, B. F. & Belmans, R., 2011. "Integrating short-term demand response into long-term investment planning," Cambridge Working Papers in Economics 1132, Faculty of Economics, University of Cambridge.
    6. Cuenca, Juan J. & Daly, Hannah E. & Hayes, Barry P., 2023. "Sharing the grid: The key to equitable access for small-scale energy generation," Applied Energy, Elsevier, vol. 349(C).
    7. Pineau, Pierre-Olivier & Rasata, Hasina & Zaccour, Georges, 2011. "Impact of some parameters on investments in oligopolistic electricity markets," European Journal of Operational Research, Elsevier, vol. 213(1), pages 180-195, August.
    8. Afful-Dadzie, Anthony & Afful-Dadzie, Eric & Awudu, Iddrisu & Banuro, Joseph Kwaku, 2017. "Power generation capacity planning under budget constraint in developing countries," Applied Energy, Elsevier, vol. 188(C), pages 71-82.
    9. Nguyen, Nhan T. & Ha-Duong, Minh, 2009. "Economic potential of renewable energy in Vietnam's power sector," Energy Policy, Elsevier, vol. 37(5), pages 1601-1613, May.
    10. Ramírez-Sagner, Gonzalo & Muñoz, Francisco D., 2019. "The effect of head-sensitive hydropower approximations on investments and operations in planning models for policy analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 105(C), pages 38-47.
    11. Cany, C. & Mansilla, C. & Mathonnière, G. & da Costa, P., 2018. "Nuclear contribution to the penetration of variable renewable energy sources in a French decarbonised power mix," Energy, Elsevier, vol. 150(C), pages 544-555.
    12. Inzunza, Andrés & Muñoz, Francisco D. & Moreno, Rodrigo, 2021. "Measuring the effects of environmental policies on electricity markets risk," Energy Economics, Elsevier, vol. 102(C).
    13. Hach, Daniel & Chyong, Chi Kong & Spinler, Stefan, 2016. "Capacity market design options: A dynamic capacity investment model and a GB case study," European Journal of Operational Research, Elsevier, vol. 249(2), pages 691-705.
    14. Woo, C.K. & Liu, Y. & Zarnikau, J. & Shiu, A. & Luo, X. & Kahrl, F., 2018. "Price elasticities of retail energy demands in the United States: New evidence from a panel of monthly data for 2001–2016," Applied Energy, Elsevier, vol. 222(C), pages 460-474.
    15. Pereira, Sérgio & Ferreira, Paula & Vaz, A.I.F., 2014. "Short-term electricity planning with increase wind capacity," Energy, Elsevier, vol. 69(C), pages 12-22.
    16. Foley, A.M. & Ó Gallachóir, B.P. & Hur, J. & Baldick, R. & McKeogh, E.J., 2010. "A strategic review of electricity systems models," Energy, Elsevier, vol. 35(12), pages 4522-4530.
    17. Daniel Hach & Stefan Spinler, 2018. "Robustness of capacity markets: a stochastic dynamic capacity investment model," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 40(2), pages 517-540, March.
    18. Yuan Liu & Qinliang Tan & Jian Han & Mingxin Guo, 2021. "Energy–Water–CO 2 Synergetic Optimization Based on a Mixed-Integer Linear Resource Planning Model Concerning the Demand Side Management in Beijing’s Power Structure Transformation," Energies, MDPI, vol. 14(11), pages 1-17, June.
    19. Anwar, Muhammad Bashar & Stephen, Gord & Dalvi, Sourabh & Frew, Bethany & Ericson, Sean & Brown, Maxwell & O’Malley, Mark, 2022. "Modeling investment decisions from heterogeneous firms under imperfect information and risk in wholesale electricity markets," Applied Energy, Elsevier, vol. 306(PA).
    20. Kjetil Haugen & Stein Wallace, 2006. "Stochastic programming: Potential hazards when random variables reflect market interaction," Annals of Operations Research, Springer, vol. 142(1), pages 119-127, February.

    More about this item

    Keywords

    ;
    ;
    ;

    JEL classification:

    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices
    • 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:ers:journl:v:xv:y:2012:i:4:p:31-46. 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: Marios Agiomavritis (email available below). General contact details of provider: https://ersj.eu/ .

    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.