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Optimal Power Management of Interconnected Microgrids Using Virtual Inertia Control Technique

Author

Listed:
  • Mahmoud Elshenawy

    (Electrical Power and Machines Engineering Department, Faculty of Engineering, Helwan University, Cairo 11792, Egypt)

  • Ashraf Fahmy

    (Faculty of Science and Engineering, Swansea University, Wales SA1 8EN, UK)

  • Adel Elsamahy

    (Electrical Power and Machines Engineering Department, Faculty of Engineering, Helwan University, Cairo 11792, Egypt
    Academy of Scientific Research and Technology (ASRT), Cairo 11792, Egypt)

  • Shaimaa A. Kandil

    (Electrical Power and Machines Engineering Department, Faculty of Engineering, Helwan University, Cairo 11792, Egypt)

  • Helmy M. El Zoghby

    (Electrical Power and Machines Engineering Department, Faculty of Engineering, Helwan University, Cairo 11792, Egypt)

Abstract

Two interconnected AC microgrids are proposed based on three renewable energy sources (RESs): wind, solar, and biogas. The wind turbine drives a permanent magnet synchronous generator (PMSG). A solar photovoltaic system (SPVS) with an appropriate inverter was incorporated. The biogas genset (BG) consists of a biogas engine coupled with a synchronous generator. Two interconnected AC microgrids, M 1 and M 2 , were considered for study in this work. The microgrid M 2 is connected to a diesel engine (DE) characterized by a continuous power supply. The distribution power loss of the interconnected AC microgrids comprises in line loss. The M 1 and M 2 losses are modeled as an objective function (OF). The power quality enhancement of the interconnected microgrids will be achieved by minimizing this OF. This research also created a unique frequency control method called virtual inertia control (VIC), which stabilizes the microgrid frequency using an optimal controller. In this paper, the following five controllers are studied: a proportional integral controller (PI), a fractional order PI controller (FOPI), a fuzzy PI controller (FPI), a fuzzy fractional order PI controller (FFOPI), and a VIC based on FFOPI controller. The five controllers were tuned using particle swarm optimization (PSO) to minimize the (OF). The main contribution of this paper is the comprehensive study of the performance of interconnected AC microgrids under step load disturbances, step changes in wind/solar input power, and eventually grid following/forming contingencies as well as the virtual inertia control of renewable energy resources used in the structure of the microgrids.

Suggested Citation

  • Mahmoud Elshenawy & Ashraf Fahmy & Adel Elsamahy & Shaimaa A. Kandil & Helmy M. El Zoghby, 2022. "Optimal Power Management of Interconnected Microgrids Using Virtual Inertia Control Technique," Energies, MDPI, vol. 15(19), pages 1-30, September.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:19:p:7026-:d:924361
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    References listed on IDEAS

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    1. Junli Deng & Yuan Mao & Yun Yang, 2020. "Distribution Power Loss Reduction of Standalone DC Microgrids Using Adaptive Differential Evolution-Based Control for Distributed Battery Systems," Energies, MDPI, vol. 13(9), pages 1-15, April.
    2. Johnson, Samuel C. & Rhodes, Joshua D. & Webber, Michael E., 2020. "Understanding the impact of non-synchronous wind and solar generation on grid stability and identifying mitigation pathways," Applied Energy, Elsevier, vol. 262(C).
    3. Fernández-Guillamón, Ana & Gómez-Lázaro, Emilio & Muljadi, Eduard & Molina-García, Ángel, 2019. "Power systems with high renewable energy sources: A review of inertia and frequency control strategies over time," Renewable and Sustainable Energy Reviews, Elsevier, vol. 115(C).
    4. Daniel Akinyele & Juri Belikov & Yoash Levron, 2018. "Challenges of Microgrids in Remote Communities: A STEEP Model Application," Energies, MDPI, vol. 11(2), pages 1-35, February.
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    Cited by:

    1. Farhad Amiri & Mohsen Eskandari & Mohammad Hassan Moradi, 2023. "Virtual Inertia Control in Autonomous Microgrids via a Cascaded Controller for Battery Energy Storage Optimized by Firefly Algorithm and a Comparison Study with GA, PSO, ABC, and GWO," Energies, MDPI, vol. 16(18), pages 1-22, September.
    2. Luis Fernando Grisales-Noreña & Bonie Johana Restrepo-Cuestas & Brandon Cortés-Caicedo & Jhon Montano & Andrés Alfonso Rosales-Muñoz & Marco Rivera, 2022. "Optimal Location and Sizing of Distributed Generators and Energy Storage Systems in Microgrids: A Review," Energies, MDPI, vol. 16(1), pages 1-30, December.

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