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Energy Routing Control Strategy for Integrated Microgrids Including Photovoltaic, Battery-Energy Storage and Electric Vehicles

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  • Yingpei Liu

    (School of Electrical and Electronic Engineering, North China Electric Power University, Baoding 071003, China)

  • Yan Li

    (School of Electrical and Electronic Engineering, North China Electric Power University, Baoding 071003, China)

  • Haiping Liang

    (School of Electrical and Electronic Engineering, North China Electric Power University, Baoding 071003, China)

  • Jia He

    (School of Electrical and Electronic Engineering, North China Electric Power University, Baoding 071003, China)

  • Hanyang Cui

    (School of Electrical and Electronic Engineering, North China Electric Power University, Baoding 071003, China)

Abstract

The Energy Internet is an inevitable trend of the development of electric power system in the future. With the development of microgrids and distributed generation (DG), the structure and operation mode of power systems are gradually changing. Energy routers are considered as key technology equipment for the development of the Energy Internet. This paper mainly studies the control of the LAN-level energy router, and discusses the structure and components of the energy router. For better control of the power transmission of an energy router, the energy routing control strategy for an integrated microgrid, including photovoltaic (PV) energy, battery-energy storage and electric vehicles (EVs) is studied. The front stage DC/DC converter of the PV system uses maximum power point tracking (MPPT) control. The constant current control is used by the bidirectional DC/DC converter of the battery-energy storage system and the EV system when they discharge. The DC/AC inverters adopt constant reactive power and constant DC voltage control. Constant current constant voltage control is adopted when an EV is charged. The control strategy model is simulated by Simulink, and the simulation results verify the feasibility and effectiveness of the proposed control strategy. The DG could generate reactive power according to the system instructions and ensure the stable output of the DC voltage of the energy router.

Suggested Citation

  • Yingpei Liu & Yan Li & Haiping Liang & Jia He & Hanyang Cui, 2019. "Energy Routing Control Strategy for Integrated Microgrids Including Photovoltaic, Battery-Energy Storage and Electric Vehicles," Energies, MDPI, vol. 12(2), pages 1-16, January.
  • Handle: RePEc:gam:jeners:v:12:y:2019:i:2:p:302-:d:198982
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    References listed on IDEAS

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    1. Mahdieh Najafzadeh & Natalia Strzelecka & Oleksandr Husev & Indrek Roasto & Kawsar Nassereddine & Dmitri Vinnikov & Ryszard Strzelecki, 2022. "Grid-Forming Operation of Energy-Router Based on Model Predictive Control with Improved Dynamic Performance," Energies, MDPI, vol. 15(11), pages 1-14, May.
    2. Miloud Rezkallah & Sanjeev Singh & Ambrish Chandra & Bhim Singh & Hussein Ibrahim, 2020. "Off-Grid System Configurations for Coordinated Control of Renewable Energy Sources," Energies, MDPI, vol. 13(18), pages 1-25, September.
    3. Sara Hebal & Djamila Mechta & Saad Harous & Mohammed Dhriyyef, 2021. "Hybrid Energy Routing Approach for Energy Internet," Energies, MDPI, vol. 14(9), pages 1-34, April.
    4. Indrek Roasto & Oleksandr Husev & Mahdiyyeh Najafzadeh & Tanel Jalakas & Jose Rodriguez, 2019. "Voltage Source Operation of the Energy-Router Based on Model Predictive Control," Energies, MDPI, vol. 12(10), pages 1-15, May.
    5. Teuvo Suntio & Tuomas Messo, 2019. "Power Electronics in Renewable Energy Systems," Energies, MDPI, vol. 12(10), pages 1-5, May.
    6. Marco Pierro & Fabio Romano Liolli & Damiano Gentili & Marcello Petitta & Richard Perez & David Moser & Cristina Cornaro, 2022. "Impact of PV/Wind Forecast Accuracy and National Transmission Grid Reinforcement on the Italian Electric System," Energies, MDPI, vol. 15(23), pages 1-28, November.

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