Faulty feeder detection based on the fluctuation characteristics of inflection point dense area for DC distribution network

A flexible direct current (DC) distribution network based on modular multilevel converter (MMC), with the advantages of no phase change failure and fewer current conversion links. It has gradually become the development trend of future medium voltage distribution networks. However, when a single-pole ground fault occurs in the feeder, the converter's low inertia and weak damping characteristics lead to a fast-rising fault current with a high peak value, which is harmful to the system. In this paper, for the difficulty of accurately selecting the faulty feeder when a single-pole ground fault occurs in a radial DC distribution network, a detection method based on the zero-mode current within the inflection point dense area (IPDA) for the fluctuation characteristics of concave and convexity (FCCC) is proposed. Firstly, the zero-mode current of each feeder is processed using a low-pass filter to select the eigen-components; Then, taking second order derivatives of the eigen-components, and the IPDA is established, to find a period in micro measurement to achieve accurate direction correspondence with opposite directions; Again, the data within IPDA is normalized; the criterion is constructed by determining each feeder's FCCC. Finally, the simulation model is built by Power Systems Computer Aided Design to verify that the method can identify the faulty feeder in various situations. Compared with existing methods, the fault detection method proposed in this paper has good stability and can withstand large grounding resistances.