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Unraveling the Black Box of Power Market Models

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  • Valeriya Azarova
  • Mathias Mier

Abstract

Detailed numerical models of power markets with millions of variables and equations are often perceived as black boxes, because differences in results cannot be traced back to single equations or assumptions, respectively. We unravel parts of those black box by determining the impact of different investment cost specifications including the role of varying discount and interest rates. We further expand our analysis to the impact of simplifications strategies (foresight, spatial resolution, temporal resolution) that are applied to contain numerical feasibility of such models. The choice of investment cost modeling (and related discount and interest rates) has the highest impact on results. Increasing or decreasing, respectively, complexity in turn, has only minor impacts. Our findings questions the current focus of the literature on complexity of power market models neglecting the most relevant factor, which is the choice of handling investment costs.

Suggested Citation

  • Valeriya Azarova & Mathias Mier, 2021. "Unraveling the Black Box of Power Market Models," ifo Working Paper Series 357, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    • Handle: RePEc:ces:ifowps:_357
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    References listed on IDEAS

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    Cited by:

    1. Mier, Mathias & Siala, Kais & Govorukha, Kristina & Mayer, Philip, 2023. "Collaboration, decarbonization, and distributional effects," Applied Energy, Elsevier, vol. 341(C).
    2. Jacqueline Adelowo & Mathias Mier & Christoph Weissbart, 2021. "Taxation of Carbon Emissions and Air Pollution in Intertemporal Optimization Frameworks with Social and Private Discount Rates," ifo Working Paper Series 360, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.

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    More about this item

    Keywords

    Energy system modeling; power market modeling; investment behavior; firm behavior; spatial resolution; temporal resolution; decarbonization;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C68 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computable General Equilibrium Models
    • Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - General
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices

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