Fault detection, classification and location methodology for solar microgrids using current injection, online phaselet transform, mathematical morphology filter and signal energy analysis

In this paper, a new method for detection and fault location and classification in MTDC solar microgrid is presented. Some issues such as expanding renewable energy sources and DC loads and efforts to increase power quality and reduce the environmental impact of electricity generation have led to the expansion of solar networks. Identifying the types and locations of faults is important to ensure service continues and to prevent further breakdowns and the increasing the protection’s selectivity characteristic. In this method, an orbital kit is connected to the network. In the fault occurrence time in the network, the fault is detected by passing a current through the connected kits and measuring the traveling waves derived from the fault current, and applying it to a mathematical morphological filter The location of the error is determined using orbital equations and flow calculations. Mathematical morphology filter output and signal energy analysis were used to determine the type of faults. The method presented in an MTDC microgrid connected to energy storage and renewable sources was tested with many faults. The results indicate the accuracy of the proposed method. This method is resistant to changes in arcs resistance (up to 100 ohms), and has a very good performance in high impedance faults conditions(up to 1000 ohms).