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Understanding Power Market Dynamics by Reflecting Market Interrelations and Flexibility-Oriented Bidding Strategies

Author

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  • Ramiz Qussous

    (Department of Sustainable Systems Engineering (INATECH), University of Freiburg, Emmy-Noether-Strasse 2, 79110 Freiburg, Germany)

  • Nick Harder

    (Department of Sustainable Systems Engineering (INATECH), University of Freiburg, Emmy-Noether-Strasse 2, 79110 Freiburg, Germany)

  • Anke Weidlich

    (Department of Sustainable Systems Engineering (INATECH), University of Freiburg, Emmy-Noether-Strasse 2, 79110 Freiburg, Germany)

Abstract

Power markets are becoming increasingly complex as they move towards (i) integrating higher amounts of variable renewable energy, (ii) shorter trading intervals and lead times, (iii) stronger interdependencies between related markets, and (iv) increasing energy system integration. For designing them appropriately, an enhanced understanding of the dynamics in interrelated short-term physical power and energy markets is required, which can be supported by market simulations. In this paper, we present an agent-based power market simulation model with rule-based bidding strategies that addresses the above-mentioned challenges, and represents market participants individually with a high level of technical detail. By allowing agents to participate in several interrelated markets, such as the energy-only market, a procurement platform for control reserve and a local heat market representing district heating systems, cross-market opportunity costs are well reflected. With this approach, we were able to reproduce EPEX SPOT market outcomes for the German bidding zone with a high level of accuracy (mean absolute percentage error of 8 €/MWh for the years 2016–2019). We were also able to model negative market prices at the energy-only market realistically, and observed that the occurrence of negative prices differs among data inputs used. The simulation model provides a useful tool for investigating different short-term physical power/energy market structures and designs in the future. The modular structure also enables extension to further related markets, such as fuel, CO 2 , or derivative markets.

Suggested Citation

  • Ramiz Qussous & Nick Harder & Anke Weidlich, 2022. "Understanding Power Market Dynamics by Reflecting Market Interrelations and Flexibility-Oriented Bidding Strategies," Energies, MDPI, vol. 15(2), pages 1-24, January.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:2:p:494-:d:722192
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    References listed on IDEAS

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    Cited by:

    1. 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.
    2. Thomas Mobius & Mira Watermeyer & Oliver Grothe & Felix Musgens, 2023. "Enhancing Energy System Models Using Better Load Forecasts," Papers 2302.11017, arXiv.org.
    3. Edgardo Cayon & Julio Sarmiento, 2022. "The Impact of Coskewness and Cokurtosis as Augmentation Factors in Modeling Colombian Electricity Price Returns," Energies, MDPI, vol. 15(19), pages 1-8, September.
    4. Shinji Kuno & Kenji Tanaka & Yuji Yamada, 2022. "Effectiveness and Feasibility of Market Makers for P2P Electricity Trading," Energies, MDPI, vol. 15(12), pages 1-24, June.
    5. Rainer Baule & Michael Naumann, 2022. "Flexible Short-Term Electricity Certificates—An Analysis of Trading Strategies on the Continuous Intraday Market," Energies, MDPI, vol. 15(17), pages 1-28, August.

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