| Abstract |
This paper proposes a data-based primary fault detection and identification (FDI) algorithm for HVDCgrids. The proposed FDI algorithm utilizes only current measurements to identify the protection zoneof the DC grid where the DC fault occurs. In contrast to the previously studied data-based methods inliterature, the proposed algorithm of this paper uses features obtained from current rather than voltagemeasurements. 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 busterminals. 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 noiseand ii) sampling frequency.The proposed algorithm is applied to a four-terminal HVDC grid. The current measurements provided tothe relays are obtained from elaborately modeled OCTs. Study results show that the proposed algorithmaccurately detects faults at DC transmission lines and converter bus terminals and identifies the protectionzone where the fault occurs (bus terminal or transmission line). The performance of the FDI algorithmdoes 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 withoutlosing accuracy is investigated. |
