Networked microgrids (NMGs) are emerging as a promising solution to enhance the resilience of power systems against climate change and natural disasters. This review provides an updated and comprehensive analysis of NMG configurations and control strategies. The study explores key aspects of NMG configurations, including formation, power distribution, and operational considerations. It also delves into NMG control features, examining their architecture, modes, and schemes. The review highlights research gaps, focusing on frequency and voltage stability, reliability, costs associated with remote switches and communication technologies, and overall network resilience. A unified approach addressing both configuration and control aspects of stable and reliable NMGs is proposed. The article outlines potential future trends, offering valuable insights for researchers in the field. The configuration of NMGs involves three key aspects: formation, power distribution, and operation. Formation involves allocating distributed energy resources (DERs), establishing boundaries, and determining physical and operational connections between microgrids. Power distribution involves conducting power flow analysis, calculating voltage magnitudes, phase angles, and power flows. Operation defines the behavior of NMGs over time under different conditions. Various methodologies are used for NMG formation, including clustering algorithms, graph theory approaches, mixed-integer programming methods, heuristic approaches, and game theory approaches. Each method has its advantages and limitations, with clustering algorithms being simple and scalable but dependent on predefined cluster numbers. Graph theory approaches, such as minimum spanning tree (MST) and breadth-first search (BFS), are used to create efficient and reliable microgrid configurations. Mixed-integer programming methods are used to optimize the configuration of NMGs, considering constraints and objectives. Heuristic approaches, such as Brute Force Search, Backtracking Search Optimization, Tabu search, Artificial Bee Colony, and Particle Swarm Optimization, are used to find approximate solutions. Game theory approaches are used to model interactions and strategic interdependence among microgrids. Power flow analysis is crucial for understanding the distribution of power within the network. Different power flow techniques are used for configuring NMGs, including AC and DC power flow analysis. The operational modes of NMGs, including grid-connected and islanded modes, require distinct methodologies for power flow analysis. The types of microgrids, such as DC, AC, and hybrid systems, significantly influence power flow analysis. The choice of network topology, such as radial grids, meshed grids, and ring grids, plays a crucial role in power flow analysis for NMGs. The operation of NMGs is divided into two primary types: predetermined networked microgrids (PNMGs) and dynamic networked microgrids (DNMGs). PNMGs maintain a consistent switching status and network configuration regardless of the system's operating conditions. DNMGs, on the other hand, have adaptable boundaries that dynamically adjust to maintain a balance between generation and load. DNMGs offer distinct advantages when compared to PNMGs, including real-time adaptabilityNetworked microgrids (NMGs) are emerging as a promising solution to enhance the resilience of power systems against climate change and natural disasters. This review provides an updated and comprehensive analysis of NMG configurations and control strategies. The study explores key aspects of NMG configurations, including formation, power distribution, and operational considerations. It also delves into NMG control features, examining their architecture, modes, and schemes. The review highlights research gaps, focusing on frequency and voltage stability, reliability, costs associated with remote switches and communication technologies, and overall network resilience. A unified approach addressing both configuration and control aspects of stable and reliable NMGs is proposed. The article outlines potential future trends, offering valuable insights for researchers in the field. The configuration of NMGs involves three key aspects: formation, power distribution, and operation. Formation involves allocating distributed energy resources (DERs), establishing boundaries, and determining physical and operational connections between microgrids. Power distribution involves conducting power flow analysis, calculating voltage magnitudes, phase angles, and power flows. Operation defines the behavior of NMGs over time under different conditions. Various methodologies are used for NMG formation, including clustering algorithms, graph theory approaches, mixed-integer programming methods, heuristic approaches, and game theory approaches. Each method has its advantages and limitations, with clustering algorithms being simple and scalable but dependent on predefined cluster numbers. Graph theory approaches, such as minimum spanning tree (MST) and breadth-first search (BFS), are used to create efficient and reliable microgrid configurations. Mixed-integer programming methods are used to optimize the configuration of NMGs, considering constraints and objectives. Heuristic approaches, such as Brute Force Search, Backtracking Search Optimization, Tabu search, Artificial Bee Colony, and Particle Swarm Optimization, are used to find approximate solutions. Game theory approaches are used to model interactions and strategic interdependence among microgrids. Power flow analysis is crucial for understanding the distribution of power within the network. Different power flow techniques are used for configuring NMGs, including AC and DC power flow analysis. The operational modes of NMGs, including grid-connected and islanded modes, require distinct methodologies for power flow analysis. The types of microgrids, such as DC, AC, and hybrid systems, significantly influence power flow analysis. The choice of network topology, such as radial grids, meshed grids, and ring grids, plays a crucial role in power flow analysis for NMGs. The operation of NMGs is divided into two primary types: predetermined networked microgrids (PNMGs) and dynamic networked microgrids (DNMGs). PNMGs maintain a consistent switching status and network configuration regardless of the system's operating conditions. DNMGs, on the other hand, have adaptable boundaries that dynamically adjust to maintain a balance between generation and load. DNMGs offer distinct advantages when compared to PNMGs, including real-time adaptability