# A Decentralized Multi-Agent-Based Approach for Low Voltage Microgrid Restoration
## 1 Introduction
### Literature Review  
The aims of restoration are to enable the power system to return to its normal conditions rapidly and securely, to minimize the losses and the restoration time, and to alleviate the adverse effects on the society after an outage. Many methods and technologies are employed for preparing the restoration schemes to address the abovementioned goals. Although the nature of the outages is unique, certain common guidelines exist to help operators restore and rebuild a stable power system after an outage [12]. The PSR can be categorized based on several different criteria as follows:  
1. Different parts of the power system: PSR needs to be carried out in different types of power systems and at different levels. In [13], the restoration of the transmission system with the goal of finding an appropriate sequence of actions to minimize the size of the blackout over time is presented. To solve the restoration ordering problem (ROP), the DC model and the linear programming approximation of AC (LPAC) power flow are used, and it is shown that the DC model is not sufficiently accurate to solve the ROP. In contrast, the LPAC power flow model is sufficiently accurate to obtain the restoration plans. In [14], the PSR is stated as a multi-objective, multi-variable, and multi-constrained nonlinear optimization problem and a multi-objective model based on the combination of the multi-agent technology and Tabu search method (TSM) is proposed for the restoration of the transmission system. Some of the studies investigate the restoration of the distribution system. In [15], by using the genetic algorithm (GA), the switching operation is minimized during the restoration process. It also reduces the required calculations time. The capabilities of the distributed generations (DGs) in distribution systems are used in [16] to minimize the restoration time and maximize the amount of restored loads. 2. Outage range: Some researchers focus on the condition in which only a small part of the power system is denergized [13] while other researchers focus on the restoration procedure after a total blackout [17]. 3. Sub problems: Much researchers have focused on the different sub problems in PSR such as generator start-up sequence [18], standing voltage phase angles [19], and selecting suitable islands to restart [20]. * Modeling: There is a trade-off between speed and accuracy of PSR analysis; capturing the behavior of the real system reduces the computation time and the implementation complexity. Both static power flow calculations [17] and dynamic electromechanical models [8; 21; 22] are used. Many recent reports focus on the using the capabilities of the MGs as the new effective solution for PSR at the distribution system level. In [8], the feasibility of MG restoration after a blackout is investigated using dynamic modeling. The microgrid central controller (MGCC) is responsible for making the restoration decisions such as starting-up the black start units, energizing the feeders, and restoring the loads and non-black start units. Using the information received periodically from the local controllers about generation and consumption levels, the centralized control system of the MG makes the restoration decisions. Such dynamic studies for MG restoration with the centralized approach are widely used in the literature. In [22], the restoration of the distribution system is investigated in the presence of multi-MGCC. Similar to [8], it is supposed that the sequence of the restoration actions is determined by the centralized control system. In [23] and [11], the dynamic studies of the centralized restoration process are performed for the MGs implemented in the northern region of Launceston in Tasmania, and Illinois Institute of Technology (IIT), respectively. The centralized control schemes are low cost and easy to design, however, they suffer from single-point-failure. Furthermore, they are not adaptive to the changes of the power network structure.