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Distributed Secondary Control for Battery Management in a DC Microgrid

Author

Listed:
  • Alexander Paul Moya

    (Department of Electrical and Electronic Engineering, Universidad de las Fuerzas Armadas (ESPE), Sangolquí 171103, Ecuador)

  • Polo Josue Pazmiño

    (Department of Electrical and Electronic Engineering, Universidad de las Fuerzas Armadas (ESPE), Sangolquí 171103, Ecuador)

  • Jacqueline Rosario Llanos

    (Department of Electrical and Electronic Engineering, Universidad de las Fuerzas Armadas (ESPE), Sangolquí 171103, Ecuador)

  • Diego Ortiz-Villalba

    (Department of Electrical and Electronic Engineering, Universidad de las Fuerzas Armadas (ESPE), Sangolquí 171103, Ecuador)

  • Claudio Burgos

    (Institute of Engineering Sciences, Universidad de O’Higgins, Rancagua 2820000, Chile)

Abstract

This research presents the design and simulation of a distributed secondary control based on a consensus algorithm for the efficient management of an isolated DC microgrid (MG-DC) that secures the distribution of active power according to the capacities of each storage unit, reducing duty cycles and extending its life cycle. The balance of powers is fulfilled through a photovoltaic (PV) generation unit and an energy storage system (ESS) based on batteries. The PV Boost converter has a maximum power point tracking (MPPT) controller based on the perturb and observe (P & O) method. In contrast, a Buck–Boost converter is integrated into each battery, which is bidirectionally controlled through a local controller and a primary droop control that balances the required power at the loads. It produces a voltage deviation on the DC bus. To compensate for this deviation, a distributed secondary control strategy based on consensus is proposed to restore the voltage while managing the power sharing according to the capacities of each battery. It allows for the improvement of its life cycle, which is shown in the state of charge (SOC) index, thus extending its life cycle. The controllers are evaluated for solar re-source changes, load changes, and different storage capacities.

Suggested Citation

  • Alexander Paul Moya & Polo Josue Pazmiño & Jacqueline Rosario Llanos & Diego Ortiz-Villalba & Claudio Burgos, 2022. "Distributed Secondary Control for Battery Management in a DC Microgrid," Energies, MDPI, vol. 15(22), pages 1-20, November.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:22:p:8769-:d:979859
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    References listed on IDEAS

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    1. Arcos-Aviles, Diego & Pascual, Julio & Guinjoan, Francesc & Marroyo, Luis & Sanchis, Pablo & Marietta, Martin P., 2017. "Low complexity energy management strategy for grid profile smoothing of a residential grid-connected microgrid using generation and demand forecasting," Applied Energy, Elsevier, vol. 205(C), pages 69-84.
    2. Pata, Ugur Korkut, 2021. "Linking renewable energy, globalization, agriculture, CO2 emissions and ecological footprint in BRIC countries: A sustainability perspective," Renewable Energy, Elsevier, vol. 173(C), pages 197-208.
    3. Chen, Chaoyi & Pinar, Mehmet & Stengos, Thanasis, 2021. "Determinants of renewable energy consumption: Importance of democratic institutions," Renewable Energy, Elsevier, vol. 179(C), pages 75-83.
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    Cited by:

    1. Jonathan Andrés Basantes & Daniela Estefanía Paredes & Jacqueline Rosario Llanos & Diego Edmundo Ortiz & Claudio Danilo Burgos, 2023. "Energy Management System (EMS) Based on Model Predictive Control (MPC) for an Isolated DC Microgrid," Energies, MDPI, vol. 16(6), pages 1-22, March.

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