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Feedback, competition and stochasticity in a day ahead electricity market

Author

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  • Giabardo, Paolo
  • Zugno, Marco
  • Pinson, Pierre
  • Madsen, Henrik

Abstract

Major recent changes in electricity markets relate to the process for their deregulation, along with increasing participation of renewable (stochastic) generation e.g. wind power. Our general objective is to model how feedback, competition and stochasticity (on the production side) interact in electricity markets, and eventually assess what their effects are on both the participants and the society. For this, day ahead electricity markets are modeled as dynamic closed loop systems, in which the feedback signal is the market price. In parallel, the Cournot competition model is considered. Mixed portfolios with significant share of renewable energy are based on stochastic threshold cost functions. Regarding trading strategies, it is assumed that generators are looking at optimizing their individual profits. The point of view of the society is addressed by analyzing market behavior and stability. The performed simulations show the beneficial effects of employing long term bidding strategies for both generators and society. Sensitivity analyses are performed in order to evaluate the effects of demand elasticity. It is shown that increase in demand elasticity reduces the possibility for the generators to exploit their market power. Furthermore, the results suggest that introduction of wind power generation in the market is beneficial both for the generators and the society.

Suggested Citation

  • Giabardo, Paolo & Zugno, Marco & Pinson, Pierre & Madsen, Henrik, 2010. "Feedback, competition and stochasticity in a day ahead electricity market," Energy Economics, Elsevier, vol. 32(2), pages 292-301, March.
    • Handle: RePEc:eee:eneeco:v:32:y:2010:i:2:p:292-301
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    2. Li, Gong & Shi, Jing & Qu, Xiuli, 2011. "Modeling methods for GenCo bidding strategy optimization in the liberalized electricity spot market–A state-of-the-art review," Energy, Elsevier, vol. 36(8), pages 4686-4700.
    3. Tomasz Sieńko & Jerzy Szczepanik, 2025. "EU Energy Markets and Renewable Energy Sources—Are We Waiting for a Crisis?," Energies, MDPI, vol. 18(15), pages 1-19, August.
    4. Qinghe Zhao & Xinyi Liu & Junlong Fang, 2023. "Extreme Gradient Boosting Model for Day-Ahead STLF in National Level Power System: Estonia Case Study," Energies, MDPI, vol. 16(24), pages 1-29, December.
    5. Li, Gong & Shi, Jing, 2012. "Agent-based modeling for trading wind power with uncertainty in the day-ahead wholesale electricity markets of single-sided auctions," Applied Energy, Elsevier, vol. 99(C), pages 13-22.

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