## 1 Introduction
In response to these challenges, this study applies the PRISMA methodology [43], ensuring a transparent and rigorous process for identifying, selecting, and analyzing relevant scientific contributions. This structured approach consolidates recent advancements, identifies remaining research gaps, and proposes directions to promote the development of intelligent, resilient, and economically sustainable smart microgrids. The analysis of the selected studies reveals that research is primarily concentrated on six interconnected thematic areas. These include the development of advanced EMSs and control architectures, highlighting the transition from centralized to distributed schemes and the growing focus on interoperability across heterogeneous systems. Another area is the integration of RES and hybrid microgrid configurations, which address technical and operational challenges associated with combining multiple generation technologies in complex hybrid AC/DC architectures. Significant efforts also focus on the deployment and optimization of advanced energy storage systems, examining both the technical performance and economic implications of hybrid storage solutions under varying demand scenarios. It is also important to recognize that the development and deployment of ad vanced energy storage systems and intelligent control strategies are strongly influenced by geographic and climatic conditions. Countries with high solar irradiance such as Australia, Spain, and parts of Latin America prioritize photovoltaic systems coupled with battery storage, while northern countries like Norway, Sweden, and Canada have focused on hybrid systems including hydro-based storage and seasonal strategies. Leading economies such as Germany, China, and the United States have developed robust energy storage and control infrastructures, often supported by progressive policies and long-term investments. These regional differences shape the technological priorities, research focus, and system-level integration strategies adopted across the globe. Therefore, understanding these contextual factors is crucial to interpreting the generalizability and applicability of the reviewed studies [44]. To meet these objectives, this paper is structured to provide a detailed analysis of current advancements and remaining challenges in smart microgrid management. This review provides a structured and thematic synthesis of recent advancements in smart microgrid management, focusing specifically on the integration of advanced energy storage systems (ESSs), intelligent control strategies, and optimization techniques. Unlike previous reviews, this study applies the PRISMA methodology to ensure transparency and replicability, and it incorporates a rigorous screening process based on five eligibility criteria. Moreover, it includes a keyword co-occurrence analysis to identify thematic clusters and current research directions. The reviewed studies, published between 2014 and 2025, reflect the most recent developments in the field. In contrast to earlier reviews that often address microgrids from a general or hardware-centric perspective, this paper emphasizes the convergence of control, prediction, and digitalization as pillars of next-generation microgrid systems. This review aims to provide a structured synthesis of recent advancements in the management and optimization of smart microgrids, with a particular focus on energy storage integration, intelligent control strategies, and predictive optimization techniques. To guide the analysis, the following research questions (RQs) were formulated: (1) What advanced energy storage configurations have been deployed in recent smart microgrid studies? (2) What types of control strategies--centralized, distributed, or adaptive--are most commonly implemented? (3) How are artificial intelligence, predictive analytics, and digital twins being used to support microgrid stability and performance? (4) What challenges and research gaps persist in achieving resilient, scalable, and secure smart microgrid operation?