Recently, there has been an increasing interest in the control community in studying large-scale distributed systems. Several techniques have been developed to address the main challenges for these systems, such as the amount of information needed to guarantee the proper operation of the system, the economic costs associated with the required communication structure, and the high computational burden of solving for the control inputs for largescale systems.

In the path to the future implementation of the smart grid, microgrids are presented as a cornerstone. An efficient and optimal microgrid operation is paramount. In this paper, we present a hierarchical microgrid management system using task sharing and an evolutionary game theory based dispatch strategy as a coordination algorithm to integrate the three main control levels needed for microgrid operation, which can be considered as a distributed intelligent system. The proposed algorithm shares the total load demanded into the distributed generators efficiently, while the microgrid utility is maximized dynamically, increasing the system reliability. Some simulation results are presented to illustrate the effectiveness of the dynamic performance of the proposed approach compared with a traditional hierarchical algorithm.

An important challenge for future energy systems is a new modeling methodology that integrates the cyber and physical components. This model must include the impact of communication networks and further cyber components, besides the relevant information of the physical system, in terms of efficiency, sustainability, reliability, security, and stability. The Cyber Physical Energy Systems (CPES) concept is presented as an interesting alternative to address this issue and its main features are identified. The main CPES research areas are identified as: modelling energy systems, energy efficiency, energy resource management, and energy control. In this work, the advantages of the CPES approach are shown in order to address current challenges in future energy systems. Smart grids, based on microgrids and distributed generation concepts, are identified as an interesting application of the CPES. A new proposal for modeling smart grids based on the CPES approach is introduced.

Energy management systems (EMS) play a crucial role in ensuring efficient and reliable operation of networked microgrids (NMGs), which have gained significant attention as a means to integrate renewable energy resources and enhance grid resilience. This paper provides an overview of energy management systems in NMGs, encompassing various aspects including system architecture, optimization algorithms, control strategies, and integration of distributed energy resources. The paper highlights the challenges and opportunities associated with energy management in NMGs and presents key approaches and technologies adopted in the field. Furthermore, it explores the implications of emerging trends such as data-driven modeling, machine learning, and advanced communication technologies on the design and performance of energy management systems in networked microgrids. Through this comprehensive overview, the paper aims to provide researchers, practitioners, and policymakers with valuable insights into the state-of-the-art developments and future directions in energy management systems for networked microgrids.