| Abstract: |
| Fault detection and classification is a key challenge for the protection of High Voltage DC (HVDC) transmission lines.
In this paper, the Teager–Kaiser Energy Operator (TKEO) algorithm associated with a decision tree-based fault classi
f
ier is proposed to detect and classify various DC faults. The Change Identification Filter is applied to the average and
differential current components, to detect the first instant of fault occurrence (above threshold) and register a Change
Identified Point (CIP). Further, if a CIP is registered for a positive or negative line, only three samples of currents (i.e.,
CIP and each side of CIP) are sent to the proposed TKEO algorithm, which produces their respective 8 indices through
which the, fault can be detected along with its classification. The new approach enables quicker detection allowing
utility grids to be restored as soon as possible. This novel approach also reduces computing complexity and the time
required to identify faults with classification. The importance and accuracy of the proposed scheme are also thor
oughly tested and compared with other methods for various faults on HVDC transmission lines. |
| Key words: Change Identification Filter, Differential current, DC faults, Simple Decision Tree, Fault classifier, HVDC
transmission link, Renewable Energy, TKEO algorithm |
| DOI：10.1186/s41601-022-00247-w |
|
| Fund:Not applicable. |
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