HESS-based microgrid control techniques empowered by artificial intelligence: A systematic review of grid-connected and standalone systems

Microgrids have the potential to support decarbonisation efforts in the electricity sector by facilitating the incorporation of more renewable energy sources. However, the inconsistent nature of renewable energy sources can hinder their effective integration. Enhancing forecasting, control, and mana...

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Bibliographic Details
Published in:Journal of energy storage 2024-04, Vol.84, p.111012, Article 111012
Main Authors: R., Shyni, Kowsalya, M.
Format: Article
Language:English
Subjects:
Artificial intelligence
Control strategies
Energy management system
Hybrid energy storage system
Microgrid
Renewable energy sources
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Summary:Microgrids have the potential to support decarbonisation efforts in the electricity sector by facilitating the incorporation of more renewable energy sources. However, the inconsistent nature of renewable energy sources can hinder their effective integration. Enhancing forecasting, control, and management systems for renewable energy generation is crucial to overcoming this challenge. Energy storage can be an effective solution, but a single storage unit may not suffice due to capacity, power, energy density, and life cycle limitations. Consequently, most researchers focus on hybrid energy storage systems that merge the most desirable attributes of multiple energy storage technologies to achieve pertinent performance. Hybrid Energy Storage System (HESS) results in control, power management, and converter design complexity. This paper discusses the existing control strategies, their drawbacks and use of artificial intelligence techniques in different control schemes, such as fuzzy logic, neural networks, and reinforcement learning pertaining to the stand alone and grid-connected microgrid. This paper also provides a comprehensive review of the various HESS configurations, power converter topologies, and energy management. Based on the literature review and existing vulnerabilities, future of artificial intelligence techniques for HESS advances in the microgrid are anticipated. •Different hybrid energy storage system combination related to microgrid is reviewed.•Detailed about bidirectional converters for HESS.•Various control techniques related to microgrid are elaborated.•Future scope of research in microgrid sectors also highlighted.
ISSN:2352-152X
2352-1538
DOI:10.1016/j.est.2024.111012