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Strategies for Controlling Microgrid Networks with Energy Storage Systems: A Review

Author

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  • Mudhafar Al-Saadi

    (School of Computing, Engineering and Digital Technologies, Teesside University, Middlesbrough TS1 3BX, UK)

  • Maher Al-Greer

    (School of Computing, Engineering and Digital Technologies, Teesside University, Middlesbrough TS1 3BX, UK)

  • Michael Short

    (School of Computing, Engineering and Digital Technologies, Teesside University, Middlesbrough TS1 3BX, UK)

Abstract

Distributed Energy Storage Systems are considered key enablers in the transition from the traditional centralized power system to a smarter, autonomous, and decentralized system operating mostly on renewable energy. The control of distributed energy storage involves the coordinated management of many smaller energy storages, typically embedded within microgrids. As such, there has been much recent interest related to controlling aspects of supporting power-sharing balance and sustainability, increasing system resilience and reliability, and balancing distributed state of charge. This paper presents a comprehensive review of decentralized, centralized, multiagent, and intelligent control strategies that have been proposed to control and manage distributed energy storage. It also highlights the potential range of services that can be provided by these storages, their control complications, and proposed solutions. Specific focus on control strategies based upon multiagent communication and reinforcement learning is a main objective of this paper, reflecting recent advancements in digitalization and AI. The paper concludes with a summary of emerging areas and presents a summary of promising future directions.

Suggested Citation

  • Mudhafar Al-Saadi & Maher Al-Greer & Michael Short, 2021. "Strategies for Controlling Microgrid Networks with Energy Storage Systems: A Review," Energies, MDPI, vol. 14(21), pages 1-45, November.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:21:p:7234-:d:670892
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    References listed on IDEAS

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    Cited by:

    1. Trinadh Pamulapati & Muhammed Cavus & Ishioma Odigwe & Adib Allahham & Sara Walker & Damian Giaouris, 2022. "A Review of Microgrid Energy Management Strategies from the Energy Trilemma Perspective," Energies, MDPI, vol. 16(1), pages 1-34, December.
    2. Maria Symeonidou & Agis M. Papadopoulos, 2022. "Selection and Dimensioning of Energy Storage Systems for Standalone Communities: A Review," Energies, MDPI, vol. 15(22), pages 1-28, November.
    3. Łukasz Mazur & Sławomir Cieślik & Stanislaw Czapp, 2023. "Trends in Locally Balanced Energy Systems without the Use of Fossil Fuels: A Review," Energies, MDPI, vol. 16(12), pages 1-31, June.
    4. Hassan Ranjbarzadeh & Seyed Masoud Moghaddas Tafreshi & Mohd Hasan Ali & Abbas Z. Kouzani & Suiyang Khoo, 2022. "A Probabilistic Model for Minimization of Solar Energy Operation Costs as Well as CO 2 Emissions in a Multi-Carrier Microgrid (MCMG)," Energies, MDPI, vol. 15(9), pages 1-24, April.
    5. Mudhafar Al-Saadi & Maher Al-Greer & Michael Short, 2023. "Reinforcement Learning-Based Intelligent Control Strategies for Optimal Power Management in Advanced Power Distribution Systems: A Survey," Energies, MDPI, vol. 16(4), pages 1-38, February.
    6. Marius Minea & Cătălin Marian Dumitrescu, 2022. "On the Feasibility and Efficiency of Self-Powered Green Intelligent Highways," Energies, MDPI, vol. 15(13), pages 1-32, June.

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