# A Decentralized Multi-Agent-Based Approach for Low Voltage Microgrid Restoration
## 4 Proposed Decentralized Approach
### Implementation of the Proposed Multi-Agent Based Approach for MG Restoration  
The function modules of the agent \(i\) is illustrated in Figure 8. Each agent has four main modules: (1) initialization; (2) information update; (3) information keep; and (4) exchange and decision making. The required steps for operation of the agents can be designated as follows:  
1. Initialization: in this step, the local initial information matrix of each agent (\(\textbf{M}_{i}^{0}\)) is formed.
2. Information sharing: in this step, each agent receives the information of its neighboring agents through a communication link and updates its information by using the ACA. After reaching the consensus, the common decision will be made.
3. Decision making: when the agents reach the consensus in the sharing information process, a proper decision will be made. Decision making is one of the crucial parts of the agents' function blocks. This block must be designed to meet the initial restoration steps such as setting up the generation units with black start capability and energizing the restoration path. Moreover, in the next steps, this block must determine a proper sequence for connection of disconnected loads and generation units by providing the maximum amount of the restored loads in the shortest possible time.  
Decision Making Process  
MG restoration process begins by setting up a generation unit with black start capability. In an inverter-based MG, the inverter with grid-forming control mode has the black start capability. It is assumed that in the MG, one inverter is in grid-forming control mode and the other ones operate in grid following mode. The output real power of the grid-following inverters is a constant value. However, the output real power of the grid-forming inverter varies based on the MG frequency (droop control). During the restoration process, the connection of a load or a generation unit changes the output power of the grid-forming inverter. The capacity and the instantaneous power of grid-forming inverter play a key role in determining a proper sequence of connecting the loads and generation units with a grid-following inverter.  
Figure 8: Function of agent \(i\) for MG restoration.  
To help better understand this, consider the flowchart of the decision making process shown in Figure 9. When the algorithm is run for the first time, the microsource with grid forming inverter is chosen and connected to energize the MG feeder. Then, a pre-defined interruption is required for damping of the frequency fluctuations. The interruption time depends on the inertia and damping factor of the MG. In the next run of the algorithm, after reaching the consensus, the information related to the output power of the grid-forming inverter \(P_{\text{form}}\) that is a small value (only for energizing the MG feeder) as well as the disconnected load units and available power of the generation units with grid-following inverter are available for all agents. The capacity of the grid-forming inverter \(P_{\text{form}}^{\text{cap}}\) is also specified. In this step, based on the discovered information, the largest possible amount of the load is chosen to be connected. This amount of the connected load makes the grid-forming inverter to work in the capacity limits, so in the next step, a generation unit with the grid-following inverter is chosen to releases the capacity of the grid-forming inverter by providing a fixed amount of power. This procedure will continue until all of the generation units and the maximum possible amount of the loads are connected.