To meet the dual requirements of selectivity and rapidity in fuse-based short-circuit protection for shipboard DC Integrated Power Systems (DC IPS), this paper proposes a novel coordination method. This approach employs an artificial neural network (ANN) to map the inherent time–current characteristic (TCC) curves of all fuses onto a unified time–current coordinate plane. Protection selectivity is then evaluated based on the relative positions of these curves, and by prioritizing fuses with shorter operating times, both selectivity and rapid fault clearance are achieved. Furthermore, through a mathematical analysis of the current relationships between faulted and non-faulted distribution circuits, the ANN is formulated to require only current and time data while maintaining robustness to moderate variations in short-circuit transition resistance. The effectiveness of the proposed method is validated using DC IPS cases of a hybrid passenger vessel and a pure electric sightseeing vessel. Compared with conventional coordination methods, the proposed method simultaneously accounts for the TCCs of protective devices and the influence of transition resistance on short-circuit current behavior. The case study results demonstrate that the proposed method achieves both selective and rapid protection, and shows strong potential for broader application in the coordination of multi-source DC power systems.
Zhang et al. (Sat,) studied this question.