• DocumentCode
    2803942
  • Title

    Medium-term flexibility options in a power plant portfolio — Energy storage units vs. thermal units

  • Author

    Genoese, Fabio ; Genoese, Massimo ; Wietschel, Martin

  • Author_Institution
    Dept. of Energy Policy & Energy Syst., Fraunhofer Inst. for Syst. & Innovations Res. ISI, Karlsruhe, Germany
  • fYear
    2012
  • fDate
    10-12 May 2012
  • Firstpage
    1
  • Lastpage
    9
  • Abstract
    Increasing the share of fluctuating renewables will require additional flexibility in the electricity system. In this paper, we present a model-based approach on how to measure the effect of additional flexibility. The agent-based market simulation model PowerACE has been enhanced to make use of optimization methods (MILP) for the unit commitment of the agents enabling us to quantify the economic benefit of flexibility at agent level. In this analysis, we compare the flexibility offered by thermal power plants to that offered by storage units for the case of existing power plant portfolios of the major German electricity generating companies. We find that for the medium-term (2020), additional storage units up to a total output of 2,000 megawatts and up to a total storage capacity of some 16,000 megawatt hours are economically more viable than gas or other fossil fuel fired power plants as they allow power plants to be dispatched in a more efficient way, i.e. less operation in part load and less start-up and shut-down events occur.
  • Keywords
    energy storage; optimisation; power engineering computing; power generation dispatch; power markets; power system simulation; thermal power stations; German electricity generating company; agent-based market simulation model PowerACE; electricity system; energy storage unit; fossil fuel fired power plant; load dispatch; medium-term flexibility option; optimization method; storage units; thermal power plant; thermal unit; unit commitment; Electricity; Energy storage; Equations; Mathematical model; Optimization; Power generation; Thermal loading; agent-based simulation; electricity market; optimization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    European Energy Market (EEM), 2012 9th International Conference on the
  • Conference_Location
    Florence
  • Print_ISBN
    978-1-4673-0834-2
  • Electronic_ISBN
    978-1-4673-0832-8
  • Type

    conf

  • DOI
    10.1109/EEM.2012.6254703
  • Filename
    6254703