# Modeling and Simulation of Autonomous DC Microgrid with Variable Droop Controller
## 2 Literature Review  
Microgrid operation is typically categorized into two distinct modes: utility-connected and autonomous. A primary challenge in autonomous operation is ensuring system stability, particularly in terms of voltage and frequency regulation. Achieving optimal power sharing between distributed generators (DGs), efficient load management, and seamless transitions between operational modes are critical for maintaining the overall stability and performance of the microgrid system [6]. Developing effective control systems enabling stable operation has been the focus of recent research, especially in islanded or autonomous mode where stability concerns are critical due to the lack of grid support [7; 8; 9]. The stability of the microgrid is intrinsically linked to the behavior of the DGs and loads, which must be carefully balanced to ensure reliable operation under varying conditions. To address these challenges, both AC and DC microgrids commonly employ a three-level hierarchical control architecture, which is essential for ensuring effective current sharing and voltage stability. In grid-connected mode, all three levels of control are required: primary, secondary, and tertiary. These controls can be implemented through either centralized or decentralized approaches. In the case of centralized control, a microgrid central controller is responsible for coordinating the operation of all components to meet the desired performance criteria. This central controller typically oversees the management of energy flow, voltage regulation, and power sharing across the system. In contrast, decentralized control involves assigning local controllers to each converter, with the stability of the microgrid maintained through cooperative communication between these local controllers. This decentralized approach can improve system resilience and reduce the dependency on a single point of failure. In islanded operation, tertiary-level control is often not required, simplifying the control structure. The primary control mechanism in DC microgrids is droop control, a well-established method for regulating power sharing and voltage stability. A virtual droop resistor is connected in series with the converter to achieve droop control, which modulates the output impedance of the power electronic converters (PECs). By adjusting the droop resistor value, the microgrid can achieve dynamic load sharing and voltage regulation without the need for centralized coordination [10]. This approach helps mitigate issues related to load imbalances and voltage deviations, thus enhancing the overall performance and reliability of the system under varying load conditions. Droop control is the most widely used and effective decentralized method for power sharing in microgrids [11]. In converter-connected microgrids, the droop characteristics of each converter can be adjusted to ensure proper load sharing among distributed generators (DGs), eliminating the need for direct communication between them, particularly in islanded operation. Microgrid control is typically structured into three hierarchical levels. Primary control is the innermost feedback and feed-forward loops that regulate voltage and frequency in real time at the converter level, ensuring local stability and load sharing. Secondary control is the level that compensates for steady-state errors, such as voltage and frequency deviations due to droop control, by adjusting reference values for the primary control through a communication network. Tertiary control manages the power exchange between microgrids or between the microgrid and the utility, optimizing energy distribution and guaranteeing seamless transitions between grid-connected and islanded modes. A comprehensive review of microgrid control and operation is presented in [12; 13], which highlight key advancements and challenges in the field. Traditional droop control strategies have been explored in [14], but these methods often fail to address voltage deviations that occur under changing load conditions.