State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources,North China Electric Power University, Beijing 102206, China

DC distribution networks have many intensive branches and few measuring points that support data high-speed communication. Meanwhile, the fault characteristics are greatly affected by the control strategy of power electronic equipment, which makes the fault location method of the traditional distribution network difficult to be applied to DC distribution network. Based on this, the paper proposes a new bipolar short-circuit fault location algorithm for DC distribution networks. According to the transient high-frequency current loop, the high-frequency impedance equivalent models of modular multilevel converter and DC/DC converter not affected by the control strategy are constructed. Then, the wavelet transform is used to extract the fault high-frequency voltage of the sparse measurement point, which is used to form the node high-frequency voltage equation. Finally, combining the equation with the Bayesian algorithm based compressed sensing theory, the node high-frequency current sparse vector is solved and fault location is achieved accurately based on sparse voltage measurement. The proposed algorithm has low requirements on the number of measuring points and is not affected by the control strategy of converters. It does not need strict data synchronization measurement and is not theoretically affected by the transition resistance. The simulation model of the 32-node DC distribution network is built in PSCAD and the location effectiveness of the proposed algorithm is verified by the test data.