A DC grid primary protection algorithm based on current measurements

This paper proposes a data-based primary fault detection and identification (FDI) algorithm for HVDC grids. The proposed FDI algorithm utilizes only current measurements to identify the protection zone of the DC grid where the DC fault occurs. In contrast to the previously studied data-based methods in literature, the proposed algorithm of this paper uses features obtained from current rather than voltage measurements. The FDI algorithms which are based on voltage measurements also require the measurements obtained from current sensors to distinguish between faults on DC transmission lines and bus terminals. This paper also presents a detailed model of an optical current transducer (OCT) and investigates how the accuracy and speed of the proposed FDI algorithm is impacted by i) measurement noise and ii) sampling frequency. The proposed algorithm is applied to a four-terminal HVDC grid. The current measurements provided to the relays are obtained from elaborately modeled OCTs. Study results show that the proposed algorithm accurately detects faults at DC transmission lines and converter bus terminals and identifies the protection zone where the fault occurs (bus terminal or transmission line). The performance of the FDI algorithm does not degrade in case of various measurement noises, i.e., optical, electronics unit, and quantization. Furthermore, the range of sampling frequency for which the proposed algorithm can be used without losing accuracy is investigated.