## 2 Methodology for Selection of Studies
### Synthesis of the Selected Studies
This word cloud highlights the frequency of recurring terms, offering valuable insights into the central themes and research trends within the dataset. The size of each term in the cloud corresponds to its frequency of appearance, reflecting the predominant topics in the reviewed studies. To guide the synthesis of the findings and uncover the structure of current research in the field, the selected studies were classified into six inter-related thematic areas. These categories emerged through a combination of word cloud analysis and conceptual alignment with the research questions of this review. Each theme addresses a key dimension of distributed energy systems and, collectively, they form an integrated narrative that spans from modeling and control to implementation and supporting technologies. Optimization and modeling provide the analytical foundation for system operation; multi-agent systems enable the decentralized execution of these models; simulations and case studies validate their practical relevance; emerging technologies such as blockchain and AI facilitate secure and automated system interactions; robust frameworks ensure reliability under uncertainty; and electric machines embody the physical components driving energy conversion and exchange. Together, these themes capture the multi-layered complexity of peer-to-peer energy management in microgrids and offer a coherent lens through which the reviewed literature is interpreted. The analysis of the word cloud enables the classification of the 94 studies into the following six broad thematic areas, each capturing a critical aspect of the research landscape:  
1. Optimization and Modeling in Energy Systems: This theme encompasses studies focused on enhancing the efficiency and sustainability of energy systems through mathematical models, advanced algorithms, and optimization techniques. Research within this category addresses co-optimization strategies for distributed energy resources, energy planning methodologies, and robust analyses to manage uncertainties in distributed generation, microgrids, and P2P energy trading. 2. Multi-Agent Systems and Distributed Control: Studies in this category explore the use of MAS and distributed control approaches for energy management. Key aspects include scalability and flexibility for coordinating energy trading in complex networks,  
Figure 5: Word cloud map built using the author’s keywords from the selected studies. such as prosumer communities and microgrids, and decentralized cooperation to enhance resilience in energy systems. 3. Simulations, Case Studies, and Real-World Applications: This theme brings together studies that validate energy management strategies and trading models through simulations to explore theoretical frameworks, case studies, and practical implementations addressing real-world challenges, experimental evidence, and insights into applying P2P systems and microgrid technologies. 4. Blockchain, Smart Contracts, and Emerging Technologies: Research in this category examines how emerging technologies enhance the functionality of energy systems. Key technologies include blockchain and smart contracts for secure, transparent, and automated transactions, AI and advanced communication tools for system optimization, applications in P2P energy markets, and prosumer networks. 5. Frameworks for Robust and Decentralized Energy Management: This category highlights the development of conceptual and methodological frameworks to improve the stability and flexibility of DES under uncertainty. Studies emphasize the decentralized coordination of energy resources and robust strategies to adapt to dynamic changes in the system operation, enhancing resilience against disruptions. 6. Electric Machines and Their Role in Distributed Energy Systems: Unlike the previous themes derived directly from the word cloud analysis, this category emerges from the specific focus of this systematic review. Based on the eight studies addressing this topic, the role of electric machines in DES is emphasized.