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Hybrid Energy Storage Systems: A Review of Topology Classification, Energy Management Strategies, Applications and Future Challenges
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DOI:10.3390/batteries12080300.png)
Abstract
En 中文
Energy storage systems (ESSs) play a crucial role in mitigating the intermittency and variability of renewable energy sources (RESs) and enhancing the stability and reliability of modern power systems. However, the inherent limitations of individual storage technologies, particularly the trade-off between energy density and power density, restrict their ability to satisfy diverse operational requirements. In this context, hybrid energy storage systems (HESSs), which combine complementary storage technologies, such as batteries, supercapacitors, and flywheels, have emerged as an effective solution capable of simultaneously delivering high-energy and high-power performance. This paper presents a comprehensive review of HESS architectures, converter topologies, energy management strategies (EMSs), and applications. The EMS taxonomy is organized into classical and intelligent control. Classical EMS approaches are categorized into filtration-based, rule-based, deadbeat, droop, sliding mode, and fuzzy logic control, whereas intelligent EMS approaches encompass optimization-based methods, including model predictive control, as well as learning-based techniques such as supervised and reinforcement learning. Moreover, HESS applications are examined across grid-scale systems, microgrids, renewable energy systems, transportation, power quality improvement, frequency regulation, peak shaving, and uninterruptible power supply systems. Representative implementations are also reviewed to identify current technological trends, operational challenges, and performance trade-offs. Finally, future research directions are outlined, with emphasis on digital twins, privacy-preserving and explainable learning frameworks, cyber–physical security, and adaptive and scalable EMSs.
Keywords:
hybrid energy storage systems
energy management
control strategies
renewable integration
Journal
B
IF:
4.8
Papers:
1.8K
Citations:
6.9K
