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A Stochastic MPC Based Energy Management System for Simultaneous Participation in Continuous and Discrete Prosumer-to-Prosumer Energy Markets

Author

Listed:
  • Pablo Baez-Gonzalez

    (Department of Systems Engineering and Automatic Control, Universidad de Sevilla, 41092 Sevilla, Spain)

  • Felix Garcia-Torres

    (Applications Unit, Centro Nacional del Hidrógeno, 13500 Puertollano, Spain)

  • Miguel A. Ridao

    (Department of Systems Engineering and Automatic Control, Universidad de Sevilla, 41092 Sevilla, Spain)

  • Carlos Bordons

    (Department of Systems Engineering and Automatic Control, Universidad de Sevilla, 41092 Sevilla, Spain)

Abstract

This article studies the exchange of self-produced renewable energy between prosumers (and with pure end consumers), through the discrete trading of energy packages and proposes a framework for optimizing this exchange. In order to mitigate the imbalances derived from discrepancies between production and consumption and their respective forecasts, the simultaneous continuous trading of instantaneous power quotas is proposed, giving rise to a time-ahead market running in parallel with a real-time one. An energy management system (EMS) based on stochastic model predictive control (SMPC) simultaneously determines the optimal bidding strategies for both markets, as well as the optimal utilisation of any energy storage system (ESS). Simulations carried out for a heterogeneous group of agents show that those with SMPC-EMS achieve savings of between 3% and 15% in their energy operation economic result. The proposed structures allows the peer-to-peer (P2P) energy trading between end users without ESS and constitute a viable alternative to avoid deviation penalties in secondary regulation markets.

Suggested Citation

  • Pablo Baez-Gonzalez & Felix Garcia-Torres & Miguel A. Ridao & Carlos Bordons, 2020. "A Stochastic MPC Based Energy Management System for Simultaneous Participation in Continuous and Discrete Prosumer-to-Prosumer Energy Markets," Energies, MDPI, vol. 13(14), pages 1-23, July.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:14:p:3751-:d:387727
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    References listed on IDEAS

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    1. Kuruseelan S & Vaithilingam C, 2019. "Peer-to-Peer Energy Trading of a Community Connected with an AC and DC Microgrid," Energies, MDPI, vol. 12(19), pages 1-15, September.
    2. Juhar Abdella & Khaled Shuaib, 2018. "Peer to Peer Distributed Energy Trading in Smart Grids: A Survey," Energies, MDPI, vol. 11(6), pages 1-22, June.
    3. Palacios-Garcia, E.J. & Moreno-Munoz, A. & Santiago, I. & Flores-Arias, J.M. & Bellido-Outeirino, F.J. & Moreno-Garcia, I.M., 2018. "A stochastic modelling and simulation approach to heating and cooling electricity consumption in the residential sector," Energy, Elsevier, vol. 144(C), pages 1080-1091.
    4. Jingpeng Yue & Zhijian Hu & Amjad Anvari-Moghaddam & Josep M. Guerrero, 2019. "A Multi-Market-Driven Approach to Energy Scheduling of Smart Microgrids in Distribution Networks," Sustainability, MDPI, vol. 11(2), pages 1-16, January.
    5. Lurian Pires Klein & Aleksandra Krivoglazova & Luisa Matos & Jorge Landeck & Manuel de Azevedo, 2019. "A Novel Peer-To-Peer Energy Sharing Business Model for the Portuguese Energy Market," Energies, MDPI, vol. 13(1), pages 1-20, December.
    6. Cristiano Codagnone & Bertin Martens, 2016. "Scoping the Sharing Economy: Origins, Definitions, Impact and Regulatory Issues," JRC Working Papers on Digital Economy 2016-01, Joint Research Centre.
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    Cited by:

    1. Mohamed Toub & Chethan R. Reddy & Rush D. Robinett & Mahdi Shahbakhti, 2021. "Integration and Optimal Control of MicroCSP with Building HVAC Systems: Review and Future Directions," Energies, MDPI, vol. 14(3), pages 1-41, January.
    2. Amrutha Raju Battula & Sandeep Vuddanti & Surender Reddy Salkuti, 2021. "Review of Energy Management System Approaches in Microgrids," Energies, MDPI, vol. 14(17), pages 1-32, September.

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