Optimal Self-healing of Smart Distribution Grids Based on Spanning Trees to Improve System Reliability

In this paper, a self-healing approach for smart distribution network is presented based on Graph theory and cut sets. In the proposed Graph theory based approach, the upstream grid and all the existing microgrids are modeled as a common node after fault occurrence. Thereafter, the maneuvering lines which are in the cut sets are selected as the recovery path for alternatives networks by making cut sets of the faulted line. After forming the candidate networks with the minimum number of switching, an unbalanced three phase power flow is performed to be assured that the new network configuration does not violate technical constraints. In the case of the constraints violation, the other candidate networks with the same number of switching or more are assessed to find a proper scheme with high loadability and low voltage unbalance values. The proposed approach is scrutinized in two different case studies: with and without microgirds connection to the distribution network. The simulation results applied on a typical distribution network in the MATLAB software show the valuable performance of the proposed approach. The using of the Graph theory has reduced the number of switching and excitation time in comparison with evolutionary search approaches.