Implementation and impact of graph theory algorithm in Z-source breaker for the protection of DC microgrid

Abstract

Abstract Integrating renewable energy resources is the solution for the power demand crisis in the power energy market, reducing carbon emissions and energy loss. Autonomous acting grids, like DC microgrids, can provide power to rural areas, which neglects grid congestion. However, a proper protection scheme still needs to be determined, as the bidirectional power flow in microgrids exists. Initially, the status of the buses in the network needs to be monitored and addressed continuously so inactive buses are identified and faulted lines are noted easily. Also, the occurrence of a fault may provide a great cause to the nearest renewable generation. So, the distance from a faulted point to the closest operating source are determined to avoid protection blinding. In this study, the active buses are identified using the Kruskal algorithm, the shortest distance from a faulted point to the nearest renewable generation for fault detection is demonstrated, and the run time is compared using Bellman Ford and Dijkstra’s algorithm. The traditional protection scheme can only do fixed relay settings, but the adaptive network works on different relay settings. The proposed system detects the fault and works based on voltage and current data at line ends. Also, the adaptive algorithm is analyzed using a bidirectional Z source breaker when implemented in nine bus DC microgrid system. Result analysis is carried out in MATLAB Simulink interfaced Python scripts for various faults, and the results prove the system’s efficiency, adaptability, and robustness.