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High Taxes on Cloudy Days: Dynamic State-Induced Price Components in Power Markets

Author

Listed:
  • Leonard Göke

    (RWTH Aachen University)

  • Reinhard Madlener

    (E.ON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN))

Abstract

In most European countries, taxes and levies, the state-induced components of electricity prices, constitute the major share of electricity prices for consumers and are charged at a fixed rate. This study analyzes whether switching stateinduced price components to time varying rates can support the integration of variable renewables (VRE) and, thus, help to efficiently achieve the overarching goal of decarbonizing the energy system. Based on game theory and linear programming, we introduce a novel simulation model of the power market. For a quantitative case study, the model is parametrized to represent a German energy system that meets the political objective to increase the share of renewables (RE) in power generation to 80% in 2050. We find that dynamization supports the integration of VRE into the energy system. Whether dynamization is an efficient instrument to promote decarbonization as well is highly dependent on the policy framework in place.

Suggested Citation

  • Leonard Göke & Reinhard Madlener, 2017. "High Taxes on Cloudy Days: Dynamic State-Induced Price Components in Power Markets," FCN Working Papers 18/2017, E.ON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN).
    • Handle: RePEc:ris:fcnwpa:2017_018
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    References listed on IDEAS

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    Cited by:

    1. Jan Martin Specht & Reinhard Madlener, 2018. "Business Models for Energy Suppliers Aggregating Flexible Distributed Assets and Policy Issues Raised," FCN Working Papers 7/2018, E.ON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN).
    2. Heesen, Florian & Madlener, Reinhard, 2021. "Revisiting heat energy consumption modeling: Household production theory applied to field experimental data," Energy Policy, Elsevier, vol. 158(C).
    3. Pereira, Guillermo Ivan & Specht, Jan Martin & Silva, Patrícia Pereira & Madlener, Reinhard, 2018. "Technology, business model, and market design adaptation toward smart electricity distribution: Insights for policy making," Energy Policy, Elsevier, vol. 121(C), pages 426-440.

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    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • C70 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - General
    • Q42 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Alternative Energy Sources
    • Q48 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Government Policy

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