| Abstract: |
| High resistance fault poses an enormous challenge to the existing algorithms of fault detection and fault classification.
In this paper, the standard deviation and accumulation method are employed to perform the fault detection and
classification. It is primarily built in two stages. Firstly, the standard deviations for the measured current’s signals of the
local and remote terminals is computed to extract the fault feature. Secondly, the cumulative approach is used to enlarge
the fault feature to perform the high resistance fault. The proposed scheme is known as Standard Deviation Index (SDI),
and it is obtained for the three phases and zero sequence. The proposed algorithm has been tested through different
fault circumstances such as multiple faults locations, fault resistances, and fault inception time. Moreover, far-end faults
with high-resistance, faults happened nearby the terminal, faults considering variable loading angle, sudden load change,
different sampling frequency, bad signaling and a fault occurred in the presence of series compensation are
also discussed. The results show that the proposed scheme performed remarkably well regarding the fault with resistance
up to 1.5kΩ and can be detected within a millisecond after the fault inception. Additionally, the computational simplicity
that characterizes the processes makes it more efficient and suitable for domain applications. |
| Key words: Power transmission line, Statistic measures, High resistance fault, Cumulative sum |
| DOI：10.1186/s41601-018-0102-4 |
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| Fund: |
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