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Optimal Participation of Heterogeneous, RES-Based Virtual Power Plants in Energy Markets

Author

Listed:
  • Oluwaseun Oladimeji

    (Institute for Research in Technology, Comillas Pontifical University, 28015 Madrid, Spain)

  • Álvaro Ortega

    (Institute for Research in Technology, Comillas Pontifical University, 28015 Madrid, Spain)

  • Lukas Sigrist

    (Institute for Research in Technology, Comillas Pontifical University, 28015 Madrid, Spain)

  • Luis Rouco

    (Institute for Research in Technology, Comillas Pontifical University, 28015 Madrid, Spain)

  • Pedro Sánchez-Martín

    (Institute for Research in Technology, Comillas Pontifical University, 28015 Madrid, Spain)

  • Enrique Lobato

    (Institute for Research in Technology, Comillas Pontifical University, 28015 Madrid, Spain)

Abstract

In this work, the optimal participation of heterogeneous, Renewable Energy Source (RES)-based Virtual Power Plant (VPP) in Day-Ahead Market (DAM) and Intra-Day Market (IDM) is studied. For this purpose, a detailed model of the RES-based VPP and of the market operation is needed. The VPP includes both dispatchable and non-dispatchable RESs and flexible demand assets. This paper presents an improved, linear solar thermal plant model to consider its non-linear efficiency curve. A novel demand model with two flexibility levels that are associated with the different market sessions is also proposed. The market operation allows for updates of energy offers and this is used by the VPP to submit DAM auctions and to participate subsequently in IDM to correct for deviations. Finally, the optimal participation of the VPP in energy markets is assessed under different weather conditions.

Suggested Citation

  • Oluwaseun Oladimeji & Álvaro Ortega & Lukas Sigrist & Luis Rouco & Pedro Sánchez-Martín & Enrique Lobato, 2022. "Optimal Participation of Heterogeneous, RES-Based Virtual Power Plants in Energy Markets," Energies, MDPI, vol. 15(9), pages 1-19, April.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:9:p:3207-:d:803788
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    References listed on IDEAS

    as
    1. Chaves-Ávila, J.P. & Fernandes, C., 2015. "The Spanish intraday market design: A successful solution to balance renewable generation?," Renewable Energy, Elsevier, vol. 74(C), pages 422-432.
    2. Shabanzadeh, Morteza & Sheikh-El-Eslami, Mohammad-Kazem & Haghifam, Mahmoud-Reza, 2016. "A medium-term coalition-forming model of heterogeneous DERs for a commercial virtual power plant," Applied Energy, Elsevier, vol. 169(C), pages 663-681.
    3. Pandžić, Hrvoje & Morales, Juan M. & Conejo, Antonio J. & Kuzle, Igor, 2013. "Offering model for a virtual power plant based on stochastic programming," Applied Energy, Elsevier, vol. 105(C), pages 282-292.
    4. Domínguez, R. & Conejo, A.J. & Carrión, M., 2014. "Operation of a fully renewable electric energy system with CSP plants," Applied Energy, Elsevier, vol. 119(C), pages 417-430.
    5. Zuoyu Liu & Weimin Zheng & Feng Qi & Lei Wang & Bo Zou & Fushuan Wen & You Xue, 2018. "Optimal Dispatch of a Virtual Power Plant Considering Demand Response and Carbon Trading," Energies, MDPI, vol. 11(6), pages 1-19, June.
    6. Herter, Karen, 2007. "Residential implementation of critical-peak pricing of electricity," Energy Policy, Elsevier, vol. 35(4), pages 2121-2130, April.
    7. Naval, Natalia & Sánchez, Raul & Yusta, Jose M., 2020. "A virtual power plant optimal dispatch model with large and small-scale distributed renewable generation," Renewable Energy, Elsevier, vol. 151(C), pages 57-69.
    8. Pandžić, Hrvoje & Kuzle, Igor & Capuder, Tomislav, 2013. "Virtual power plant mid-term dispatch optimization," Applied Energy, Elsevier, vol. 101(C), pages 134-141.
    9. Hungerford, Zoe & Bruce, Anna & MacGill, Iain, 2019. "The value of flexible load in power systems with high renewable energy penetration," Energy, Elsevier, vol. 188(C).
    Full references (including those not matched with items on IDEAS)

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