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Hybrid Microgrid Energy Management and Control Based on Metaheuristic-Driven Vector-Decoupled Algorithm Considering Intermittent Renewable Sources and Electric Vehicles Charging Lot

Author

Listed:
  • Tawfiq M. Aljohani

    (Energy Systems Research Laboratory, Department of Electrical and Computer Engineering, Florida International University, Miami, FL 33174, USA)

  • Ahmed F. Ebrahim

    (Energy Systems Research Laboratory, Department of Electrical and Computer Engineering, Florida International University, Miami, FL 33174, USA)

  • Osama Mohammed

    (Energy Systems Research Laboratory, Department of Electrical and Computer Engineering, Florida International University, Miami, FL 33174, USA)

Abstract

Energy management and control of hybrid microgrids is a challenging task due to the varying nature of operation between AC and DC components which leads to voltage and frequency issues. This work utilizes a metaheuristic-based vector-decoupled algorithm to balance the control and operation of hybrid microgrids in the presence of stochastic renewable energy sources and electric vehicles charging structure. The AC and DC parts of the microgrid are coupled via a bidirectional interlinking converter, with the AC side connected to a synchronous generator and portable AC loads, while the DC side is connected to a photovoltaic system and an electric vehicle charging system. To properly ensure safe and efficient exchange of power within allowable voltage and frequency levels, the vector-decoupled control parameters of the bidirectional converter are tuned via hybridization of particle swarm optimization and artificial physics optimization. The proposed control algorithm ensures the stability of both voltage and frequency levels during the severe condition of islanding operation and high pulsed demands conditions as well as the variability of renewable source production. The proposed methodology is verified in a state-of-the-art hardware-in-the-loop testbed. The results show robustness and effectiveness of the proposed algorithm in managing the real and reactive power exchange between the AC and DC parts of the microgrid within safe and acceptable voltage and frequency levels.

Suggested Citation

  • Tawfiq M. Aljohani & Ahmed F. Ebrahim & Osama Mohammed, 2020. "Hybrid Microgrid Energy Management and Control Based on Metaheuristic-Driven Vector-Decoupled Algorithm Considering Intermittent Renewable Sources and Electric Vehicles Charging Lot," Energies, MDPI, vol. 13(13), pages 1-19, July.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:13:p:3423-:d:379635
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    References listed on IDEAS

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    1. Farahat, M.A. & Metwally, H.M.B. & Abd-Elfatah Mohamed, Ahmed, 2012. "Optimal choice and design of different topologies of DC–DC converter used in PV systems, at different climatic conditions in Egypt," Renewable Energy, Elsevier, vol. 43(C), pages 393-402.
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    4. Christos-Spyridon Karavas & Konstantinos Arvanitis & George Papadakis, 2017. "A Game Theory Approach to Multi-Agent Decentralized Energy Management of Autonomous Polygeneration Microgrids," Energies, MDPI, vol. 10(11), pages 1-22, November.
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    Cited by:

    1. Abdellatif Elmouatamid & Radouane Ouladsine & Mohamed Bakhouya & Najib El Kamoun & Mohammed Khaidar & Khalid Zine-Dine, 2020. "Review of Control and Energy Management Approaches in Micro-Grid Systems," Energies, MDPI, vol. 14(1), pages 1-30, December.
    2. Kaur, Sachpreet & Kaur, Tarlochan & Khanna, Rintu, 2022. "Design of the ANFIS based optimized frequency control module for an electric vehicle charging station," Applied Energy, Elsevier, vol. 326(C).
    3. Hong Li & Yang Liu & Jianfeng Yang, 2021. "A Novel FCS-MPC Method of Multi-Level APF Is Proposed to Improve the Power Quality in Renewable Energy Generation Connected to the Grid," Sustainability, MDPI, vol. 13(8), pages 1-14, April.
    4. Wooyoung Jeon & Sangmin Cho & Seungmoon Lee, 2020. "Estimating the Impact of Electric Vehicle Demand Response Programs in a Grid with Varying Levels of Renewable Energy Sources: Time-of-Use Tariff versus Smart Charging," Energies, MDPI, vol. 13(17), pages 1-22, August.
    5. Younes Zahraoui & Ibrahim Alhamrouni & Saad Mekhilef & M. Reyasudin Basir Khan & Mehdi Seyedmahmoudian & Alex Stojcevski & Ben Horan, 2021. "Energy Management System in Microgrids: A Comprehensive Review," Sustainability, MDPI, vol. 13(19), pages 1-33, September.
    6. Muhammad Shahab & Shaorong Wang & Abdul Khalique Junejo, 2021. "Improved Control Strategy for Three-Phase Microgrid Management with Electric Vehicles Using Multi Objective Optimization Algorithm," Energies, MDPI, vol. 14(4), pages 1-23, February.

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