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Energy Management System (EMS) Based on Model Predictive Control (MPC) for an Isolated DC Microgrid

Author

Listed:
  • Jonathan Andrés Basantes

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

  • Daniela Estefanía Paredes

    (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 Edmundo Ortiz

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

  • Claudio Danilo Burgos

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

Abstract

Microgrids have become an alternative for integrating distributed generation to supply energy to isolated communities, so their control and optimal management are important. This research designs and simulates the three levels of control of a DC microgrid operating in isolated mode and proposes an Energy Management System (EMS) based on Model Predictive Control (MPC), with real-time measurement feedback for optimal energy dispatch, which ensures power flow distribution and operation at minimum cost while extending the lifespan of the BESS. The EMS can react to disturbances produced in the lower control levels. The microgrid’s performance is analyzed and compared in two scenarios without EMS, and with EMS against changes in irradiation and changes in electricity demand. The fulfillment of the power balance is evaluated by analyzing the power delivered by each generation unit, the operating cost, and the state of charge of the battery (SOC).

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:6:p:2912-:d:1103942
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    References listed on IDEAS

    as
    1. Khairy Sayed & Ahmed G. Abo-Khalil & Ali S. Alghamdi, 2019. "Optimum Resilient Operation and Control DC Microgrid Based Electric Vehicles Charging Station Powered by Renewable Energy Sources," Energies, MDPI, vol. 12(22), pages 1-23, November.
    2. 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.
    3. Maria Fotopoulou & Dimitrios Rakopoulos & Dimitrios Trigkas & Fotis Stergiopoulos & Orestis Blanas & Spyros Voutetakis, 2021. "State of the Art of Low and Medium Voltage Direct Current (DC) Microgrids," Energies, MDPI, vol. 14(18), pages 1-27, September.
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    Cited by:

    1. Tushar Kanti Roy & Amanullah Maung Than Oo & Subarto Kumar Ghosh, 2024. "Designing a High-Order Sliding Mode Controller for Photovoltaic- and Battery Energy Storage System-Based DC Microgrids with ANN-MPPT," Energies, MDPI, vol. 17(2), pages 1-22, January.
    2. Ahmed Rashwan & Alexey Mikhaylov & Tomonobu Senjyu & Mahdiyeh Eslami & Ashraf M. Hemeida & Dina S. M. Osheba, 2023. "Modified Droop Control for Microgrid Power-Sharing Stability Improvement," Sustainability, MDPI, vol. 15(14), pages 1-19, July.
    3. Escobar, Eros D. & Betancur, Daniel & Manrique, Tatiana & Isaac, Idi A., 2023. "Model predictive real-time architecture for secondary voltage control of microgrids," Applied Energy, Elsevier, vol. 345(C).

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