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Distribution-Level Flexibility Market for Congestion Management

Author

Listed:
  • Ayman Esmat

    (Department of Electrical Engineering, Universidad Carlos III de Madrid, Avenida de la Universidad 30, 28911 Leganés, Madrid, Spain)

  • Julio Usaola

    (Department of Electrical Engineering, Universidad Carlos III de Madrid, Avenida de la Universidad 30, 28911 Leganés, Madrid, Spain)

  • María Ángeles Moreno

    (Department of Electrical Engineering, Universidad Carlos III de Madrid, Avenida de la Universidad 30, 28911 Leganés, Madrid, Spain)

Abstract

Nowadays, problems facing Distribution System Operators (DSOs) due to demand increase and the wide penetration of renewable energy are usually solved by means of grid reinforcement. However, the smart grid paradigm enables the deployment of demand flexibility for congestion management in distribution grids. This could substitute, or at least postpone, these needed investments. A key role in this scheme is the aggregator, who can act as a “flexibility provider” collecting the available flexibility from the consumers. Under this paradigm, this paper proposes a flexibility market led by the DSO and aimed at solving distribution grid congestions. The proposal also includes a flexibility market clearing algorithm, which is easy to implement, has low computational requirements and considers the energy rebound effect. The proposed design has the advantage of excluding the DSO’s need for trading in energy markets. Also, the solution algorithm proposed is fully compatible with already existing grid analysis tools. The proposed electricity market is tested with two case studies from a real Spanish distribution network, where the proposed clearing algorithm is used, and finally, results are presented and discussed.

Suggested Citation

  • Ayman Esmat & Julio Usaola & María Ángeles Moreno, 2018. "Distribution-Level Flexibility Market for Congestion Management," Energies, MDPI, vol. 11(5), pages 1-24, April.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:5:p:1056-:d:143215
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    References listed on IDEAS

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    Cited by:

    1. Schreiner, Lena & Madlener, Reinhard, 2022. "Investing in power grid infrastructure as a flexibility option: A DSGE assessment for Germany," Energy Economics, Elsevier, vol. 107(C).
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    3. Erik Heilmann & Nikolai Klempp & Kai Hufendiek & Heike Wetzel, 2022. "Long-term Contracts for Network-supportive Flexibility in Local Flexibility Markets," MAGKS Papers on Economics 202224, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    4. Ricardo Silva & Everton Alves & Ricardo Ferreira & José Villar & Clara Gouveia, 2021. "Characterization of TSO and DSO Grid System Services and TSO-DSO Basic Coordination Mechanisms in the Current Decarbonization Context," Energies, MDPI, vol. 14(15), pages 1-30, July.
    5. Ayman Esmat & Julio Usaola & Mª Ángeles Moreno, 2018. "A Decentralized Local Flexibility Market Considering the Uncertainty of Demand," Energies, MDPI, vol. 11(8), pages 1-32, August.
    6. Andreas Zeiselmair & Simon Köppl, 2021. "Constrained Optimization as the Allocation Method in Local Flexibility Markets," Energies, MDPI, vol. 14(13), pages 1-21, June.
    7. Shantanu Chakraborty & Remco Verzijlbergh & Kyri Baker & Milos Cvetkovic & Laurens De Vries & Zofia Lukszo, 2020. "A Coordination Mechanism For Reducing Price Spikes in Distribution Grids," Energies, MDPI, vol. 13(10), pages 1-24, May.
    8. Ghaemi, Sina & Li, Xinyu & Mulder, Machiel, 2023. "Economic feasibility of green hydrogen in providing flexibility to medium-voltage distribution grids in the presence of local-heat systems," Applied Energy, Elsevier, vol. 331(C).
    9. Javier Leiva & Rubén Carmona Pardo & José A. Aguado, 2019. "Data Analytics-Based Multi-Objective Particle Swarm Optimization for Determination of Congestion Thresholds in LV Networks," Energies, MDPI, vol. 12(7), pages 1-20, April.
    10. Aguado, José A. & Paredes, Ángel, 2023. "Coordinated and decentralized trading of flexibility products in Inter-DSO Local Electricity Markets via ADMM," Applied Energy, Elsevier, vol. 337(C).
    11. Aleksandra Baczyńska & Waldemar Niewiadomski, 2020. "Power Flow Tracing for Active Congestion Management in Modern Power Systems," Energies, MDPI, vol. 13(18), pages 1-25, September.
    12. Carlo Schmitt & Felix Gaumnitz & Andreas Blank & Olivier Rebenaque & Théo Dronne & Arnault Martin & Philippe Vassilopoulos & Albert Moser & Fabien Roques, 2021. "Framework for Deterministic Assessment of Risk-Averse Participation in Local Flexibility Markets †," Energies, MDPI, vol. 14(11), pages 1-34, May.
    13. Thomas Pownall & Iain Soutar & Catherine Mitchell, 2021. "Re-Designing GB’s Electricity Market Design: A Conceptual Framework Which Recognises the Value of Distributed Energy Resources," Energies, MDPI, vol. 14(4), pages 1-26, February.
    14. Heinrich, Carsten & Ziras, Charalampos & Syrri, Angeliki L.A. & Bindner, Henrik W., 2020. "EcoGrid 2.0: A large-scale field trial of a local flexibility market," Applied Energy, Elsevier, vol. 261(C).
    15. Jin, Xiaolong & Wu, Qiuwei & Jia, Hongjie, 2020. "Local flexibility markets: Literature review on concepts, models and clearing methods," Applied Energy, Elsevier, vol. 261(C).
    16. Bochun Zhan & Changsen Feng & Zhemin Lin & Xiaoyu Shao & Fushuan Wen, 2023. "Peer-to-Peer Energy Trading among Prosumers with Voltage Regulation Services Provision," Energies, MDPI, vol. 16(14), pages 1-22, July.
    17. Gržanić, Mirna & Capuder, Tomislav, 2023. "Collaboration model between Distribution System Operator and flexible prosumers based on a unique dynamic price for electricity and flexibility," Applied Energy, Elsevier, vol. 350(C).
    18. Babagheibi, Mahsa & Jadid, Shahram & Kazemi, Ahad, 2023. "An Incentive-based robust flexibility market for congestion management of an active distribution system to use the free capacity of Microgrids," Applied Energy, Elsevier, vol. 336(C).

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