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The arithmetic of stepwise offer curves

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  • Mestre, Guillermo
  • Sánchez-Úbeda, Eugenio F.
  • Muñoz San Roque, Antonio
  • Alonso, Estrella

Abstract

In liberalized electricity markets, aggregated stepwise supply and demand curves are at the core of many relevant processes. Efficient and meaningful representations of the offer curves is an essential procedure for agents participating in those markets. However, there is not a formal framework that allows operating with those offer curves using basic arithmetic operations. In this paper we first formalize the concept of stepwise offer curve by explicitly defining the standard True Offer Curve (TOC). To overcome the inherit difficulties of this non-continuous TOC, we propose the Encoded Offer Curve (EOC), a continuous piecewise version that approximates the steps of the TOC with high accuracy. We present fast and simple specialized algorithms to obtain both TOC and EOC models, as well as a formal framework to deal with elementary mathematical operations involving TOCs and EOCs. The proposed framework has been tested in the Italian electricity market, computing the residual demand curves of the producers in a particular Market Zone; and in the Iberian electricity market, quantifying the differences in the bidding behavior of market agents in different stages of the COVID-19 pandemic.

Suggested Citation

  • Mestre, Guillermo & Sánchez-Úbeda, Eugenio F. & Muñoz San Roque, Antonio & Alonso, Estrella, 2022. "The arithmetic of stepwise offer curves," Energy, Elsevier, vol. 239(PE).
  • Handle: RePEc:eee:energy:v:239:y:2022:i:pe:s0360544221026931
    DOI: 10.1016/j.energy.2021.122444
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    References listed on IDEAS

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    1. Ziel, Florian & Steinert, Rick, 2016. "Electricity price forecasting using sale and purchase curves: The X-Model," Energy Economics, Elsevier, vol. 59(C), pages 435-454.
    2. Paul L. Joskow, 2008. "Lessons Learned from Electricity Market Liberalization," The Energy Journal, International Association for Energy Economics, vol. 0(Special I), pages 9-42.
    3. Sahraei-Ardakani, Mostafa & Blumsack, Seth & Kleit, Andrew, 2015. "Estimating zonal electricity supply curves in transmission-constrained electricity markets," Energy, Elsevier, vol. 80(C), pages 10-19.
    4. 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.
    5. Florian Ziel & Rick Steinert, 2015. "Electricity Price Forecasting using Sale and Purchase Curves: The X-Model," Papers 1509.00372, arXiv.org, revised Aug 2016.
    6. Zare, Kazem & Moghaddam, Mohsen Parsa & Sheikh El Eslami, Mohammad Kazem, 2010. "Demand bidding construction for a large consumer through a hybrid IGDT-probability methodology," Energy, Elsevier, vol. 35(7), pages 2999-3007.
    7. Davatgaran, Vahid & Saniei, Mohsen & Mortazavi, Seyed Saeidollah, 2018. "Optimal bidding strategy for an energy hub in energy market," Energy, Elsevier, vol. 148(C), pages 482-493.
    8. Ross Baldick & Ryan Grant & Edward Kahn, 2004. "Theory and Application of Linear Supply Function Equilibrium in Electricity Markets," Journal of Regulatory Economics, Springer, vol. 25(2), pages 143-167, March.
    9. Ferruzzi, Gabriella & Cervone, Guido & Delle Monache, Luca & Graditi, Giorgio & Jacobone, Francesca, 2016. "Optimal bidding in a Day-Ahead energy market for Micro Grid under uncertainty in renewable energy production," Energy, Elsevier, vol. 106(C), pages 194-202.
    10. RUIZ, Carlos & CONEJO, Antonio J. & SMEERS, Yves, 2012. "Equilibria in an oligopolistic electricity pool with stepwise offer curves," LIDAM Reprints CORE 2395, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    11. Kimbrough, Steven O. & Murphy, Frederic H., 2013. "Strategic bidding of offer curves: An agent-based approach to exploring supply curve equilibria," European Journal of Operational Research, Elsevier, vol. 229(1), pages 165-178.
    12. Al-Agtash, Salem Y., 2010. "Supply curve bidding of electricity in constrained power networks," Energy, Elsevier, vol. 35(7), pages 2886-2892.
    13. Ottesen, Stig Ødegaard & Tomasgard, Asgeir & Fleten, Stein-Erik, 2018. "Multi market bidding strategies for demand side flexibility aggregators in electricity markets," Energy, Elsevier, vol. 149(C), pages 120-134.
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