High Frequency Transient Sparse Measurement-Based Fault Location for Complex DC Distribution Networks

Abstract

Measurement points supporting data high-speed communication in complex dc distribution networks are insufficient, meanwhile, fault characteristics are greatly affected by control strategies of power electronic equipment. These may cause failure of traditional fault location methods when applied to complex dc distribution networks. Thus, this paper proposes a novel dc pole-to-pole short-circuit fault location algorithm for complex dc distribution networks. First, according to the high frequency transient current loops, this paper constructs the high frequency impedance equivalent models of module multilevel converter (MMC) and dc/dc converter, which are not affected by the control strategies and offer stable impedance values during fault process. Then high frequency transient voltages of sparse measurement points are extracted by wavelet transform to form the node high frequency transient voltage equation. Finally, the node high frequency transient current sparse vector is solved to locate fault position by the node high frequency transient voltage equation combined with the Bayesian compressed sensing (BCS) theory. The proposed algorithm has low requirements on the number of measurement points and does not require data to be measured strictly synchronously. It is also not affected by converter’s control strategies and transition resistances. A 32-node dc distribution network is built in PSCAD/EMTDC and simulation results verify the accuracy of the proposed location algorithm.