# Networked Microgrids: A Review on Configuration, Operation, and Control Strategies
## 3 Networked Microgrids' Control
### Control
#### 3.2.3 Control Schemes  
Control schemes within the context of networked microgrids can be categorized into several main types: hierarchical control schemes, droop-based control, optimization-based techniques, and artificial intelligence-based methods. Hierarchical control schemes are organized systems that divide control responsibilities into three layers--primary, secondary, and tertiary. This structuring aims to standardize the operation of microgrids, enhancing their overall resilience [169]. While the primary goal of hierarchical control is to effectively manage network frequency and voltage by fostering collaboration among distributed energy sources, it has introduced several challenges within power control systems. These challenges are particularly associated with the integration of power electronics, telecommunications, fault monitoring, and security considerations. The primary control level is responsible for ensuring the reliable operation of networked microgrid components in real time. It primarily deals with tasks like maintaining voltage and frequency within acceptable limits [164], load sharing among microgrid components [163], power transactions between microgrids [114; 162], and responding to immediate disturbances [165]. Primary control operates at a fast timescale, typically in the range of milliseconds to seconds, and focuses on maintaining the microgrid's stability. Secondary control operates at a slower timescale, often in the range of minutes to hours. It aims to synchronize the interconnecting microgrids by regulating the voltage and frequency in response to variations in load and energy supply [114; 162; 166]. This level of control is responsible for optimizing the operation of microgrid components and ensuring efficient energy distribution. The tertiary control level deals with the long-term planning and optimization of networked microgrids. It focuses on coordinating the flow of power between the microgrid and the main grid [167], optimizing resource allocation [170], and ensuring cost effectiveness [161]. Tertiary control operates at timescales ranging from hours to days and even weeks. Droop-based control, primarily implemented at the secondary control layer, involves setting droop characteristics for components like generators and inverters. These characteristics aid in load sharing and maintain voltage and frequency stability amidst variations. The dynamic model for the droop controller is applied across the entire microgrid, discussed in both small-scale [171; 175] and large-scale [172; 173; 174] scenarios. This control strategy simplifies structures and reduces reliance on communication systems, as demonstrated in references [176; 177; 178]. However, in islanded microgrids using droop-based control, a challenge arises in ensuring voltage and frequency stability without a main grid [179]. This is due to the absence of slack buses, changing control modes of DERs, dynamic microgrid structures, and stringent data privacy requirements. Various approaches, like the adaptive droop-based controllers [180; 181; 182], predictive model [183; 104], and enhancements to the droop-based primary controller through a secondary controller [184], are proposed to address this challenge. Optimization-based control strategies in NMGs often leverage optimization methods to enhance the efficiency, reliability, and economic viability of the DERs within the interconnected microgrid system. These optimization-based control schemes utilize math ematical algorithms such as MILP [112; 113; 137; 141; 185; 192], MISOCP [186], two-stage robust MIP [109; 142], heuristic algorithm [123; 140; 187], optimal power flow [110; 138; 139], and game theory [188; 189; 190; 188] to determine the optimal setpoints for various operational parameters, including bus voltage [137; 138; 186], feeder power loss [137; 138; 185], risk index [140; 192], resilience level [109], thermal rates of distribution lines [112], power sharing [113; 139], active and reactive power [110], and the coordination of demand response [141; 142].