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Modelling start-up costs of multiple technologies in electricity markets

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  • Ludwig Kuntz
  • Felix Müsgens

Abstract

This paper deals with the dispatch problem in providing electric power with minimal costs using different technologies. Initially, we describe this problem in terms of a linear program. This enables us to take generally neglected start-up costs into account. The main result is the explicit solution of a simplified linear program which provides us with a better understanding of the ‘start-up cost’ effects. Furthermore, we show that dominated technologies should be used in the case of limited availability of efficient technologies. Copyright Springer-Verlag 2007

Suggested Citation

  • Ludwig Kuntz & Felix Müsgens, 2007. "Modelling start-up costs of multiple technologies in electricity markets," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 66(1), pages 21-32, August.
    • Handle: RePEc:spr:mathme:v:66:y:2007:i:1:p:21-32
    DOI: 10.1007/s00186-007-0148-y
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    References listed on IDEAS

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    1. Jonathan F. Bard, 1988. "Short-Term Scheduling of Thermal-Electric Generators Using Lagrangian Relaxation," Operations Research, INFORMS, vol. 36(5), pages 756-766, October.
    2. O'Neill, Richard P. & Sotkiewicz, Paul M. & Hobbs, Benjamin F. & Rothkopf, Michael H. & Stewart, William R., 2005. "Efficient market-clearing prices in markets with nonconvexities," European Journal of Operational Research, Elsevier, vol. 164(1), pages 269-285, July.
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    Citations

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    Cited by:

    1. De Jonghe, Cedric & Delarue, Erik & Belmans, Ronnie & D'haeseleer, William, 2011. "Determining optimal electricity technology mix with high level of wind power penetration," Applied Energy, Elsevier, vol. 88(6), pages 2231-2238, June.
    2. 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.
    3. Müsgens, Felix, 2020. "Equilibrium prices and investment in electricity systems with CO2-emission trading and high shares of renewable energies," Energy Economics, Elsevier, vol. 86(C).
    4. Abrell, Jan & Kunz, Friedrich & Weigt, Hannes, 2008. "Start Me Up: Modeling of Power Plant Start-Up Conditions and their Impact on Prices," MPRA Paper 65661, University Library of Munich, Germany.
    5. Thure Traber & Claudia Kemfert, 2012. "Vom Winde verweht? Strommarktpreise und Anreize zur Investition in thermische Kraftwerke bei erhöhtem Angebot an Windenergie," Vierteljahrshefte zur Wirtschaftsforschung / Quarterly Journal of Economic Research, DIW Berlin, German Institute for Economic Research, vol. 81(1), pages 91-110.
    6. Ellen Krohn Aasgård, 2017. "Hydropower Bidding Using Linearized Start-Ups," Energies, MDPI, vol. 10(12), pages 1-13, November.
    7. Mira Watermeyer & Thomas Mobius & Oliver Grothe & Felix Musgens, 2023. "A hybrid model for day-ahead electricity price forecasting: Combining fundamental and stochastic modelling," Papers 2304.09336, arXiv.org.
    8. Traber, Thure & Kemfert, Claudia, 2011. "Gone with the wind? -- Electricity market prices and incentives to invest in thermal power plants under increasing wind energy supply," Energy Economics, Elsevier, vol. 33(2), pages 249-256, March.

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    More about this item

    Keywords

    Electricity markets; Energy modeling; C61; Q41;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices

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