Analysis highlights the role of artificial intelligence and blockchain in enhancing energy management and storage efficiency in microgrids, supporting decentralized control systems.
This paper examines artificial intelligence and blockchain applications for optimizing energy in multi‐energy microgrids. It begins with historical energy context and the need for efficient microgrid solutions. The study reviews different energy resources and their conversion processes, followed by an in‐depth review of the advanced energy storage systems, including battery, supercapacitor, superconducting magnetic, fuel cell, flywheel, and hybrid energy storage systems. Control of microgrid systems is analyzed for centralized, decentralized, distributed, hierarchical, and predictive controls, discussing their advantages and limitations. Modern control strategies based on artificial intelligence and blockchain are critically reviewed and compared. Artificial intelligence used in microgrid (MG) is discussed in detail, which improves scalability, resilience, and efficiency. Machine learning techniques employed in MG are discussed which enhance the accuracy of predictions in terms of energy distribution, demand, and stability. Finally, around 125 research publications on the subject are also appended for quick reference.
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Bilal et al. (2025) studied this question.
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