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Consumer Theory-Based Primary Frequency Regulation in Multi-Microgrid Systems within a P2P Energy Management Framework

Author

Listed:
  • Dagoberto Martinez-Polo

    (Department of Electrical and Electronic Engineering, Universidad Nacional de Colombia, Bogota 111321, Colombia)

  • David Romero-Quete

    (Department of Electrical and Electronic Engineering, Universidad Nacional de Colombia, Bogota 111321, Colombia)

  • Camilo A. Cortes

    (Department of Electrical and Electronic Engineering, Universidad Nacional de Colombia, Bogota 111321, Colombia)

Abstract

This paper presents a novel primary frequency regulation strategy for multi-microgrid (MMG) systems, utilizing consumer theory within a peer-to-peer (P2P) energy management framework. By coordinating photovoltaic (PV) systems and energy storage systems (ESS), the proposed method ensures a rapid and effective response to frequency deviations. Unlike conventional approaches, this strategy minimizes the curtailment of renewable energy sources by prioritizing the use of ESS, allowing excess energy to charge the ESS for later use during under-frequency events. This not only enhances energy efficiency but also maximizes renewable energy utilization. Simulations demonstrate that the proposed scheme achieves lower frequency deviations and faster stabilization compared to traditional droop and virtual inertia methods. These results highlight the potential benefits of integrating consumer theory-based models into primary frequency regulation, significantly enhancing system stability and efficiency in power systems with high levels of renewable energy penetration.

Suggested Citation

  • Dagoberto Martinez-Polo & David Romero-Quete & Camilo A. Cortes, 2024. "Consumer Theory-Based Primary Frequency Regulation in Multi-Microgrid Systems within a P2P Energy Management Framework," Sustainability, MDPI, vol. 16(15), pages 1-22, August.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:15:p:6655-:d:1449433
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    References listed on IDEAS

    as
    1. Li, Zhengmao & Wu, Lei & Xu, Yan & Wang, Luhao & Yang, Nan, 2023. "Distributed tri-layer risk-averse stochastic game approach for energy trading among multi-energy microgrids," Applied Energy, Elsevier, vol. 331(C).
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