Abstract
For fast and accurate faulty line selection (FLS) in single phase-to-ground (SPG) faults for resonant grounded distribution networks (RGDNs), this paper proposes a FLS method based on zero-sequence power characteristics. Through analysis of the zero-sequence current of SPG faults, it is found that the transient zero-sequence current in the faulty line contains abundant attenuated DC components, while that in the sound line is weak, which could be utilized as a technically practical way of judging faulty lines. Thus a FLS scheme using a transient zero-sequence DC component energy integral is put forward, which highlights the difference of the DC components in the faulty line and the sound line. A series of simulation test results indicate that the proposed scheme shows favorable performance under various SPG fault conditions, and should be helpful to improve the success rate of FLS significantly for RGDN in the future.
Highlights
Nowadays, most medium voltage distribution networks in China employ an ineffectively grounded neutral to reduce overvoltage caused by single phase-to-ground (SPG) faults [1,2]
When a SPG fault occurs, the anti-arc coil over-compensates the total capacitive current in the network, and the residual fault current is not seriously harmful to the power supply equipment in a short time, but on the other hand it may leads to deadly consequences if the faulty line is not isolated from the distribution network in time, so it is very necessary to detect and isolate the faulty line automatically to ensure the reliability of the distribution automation and power supply
It can be seen from Equation (9), in the condition of a SPG fault in resonant grounded distribution networks (RGDNs), the DC component of the zero-sequence current of the faulty line is much larger than that of the sound line, so a large number of DC components only constitute a loop between the anti-arc coil, the faulty line and the grounding resistance
Summary
Most medium voltage distribution networks in China employ an ineffectively grounded (i.e., isolated or a anti-arc coil grounded) neutral to reduce overvoltage caused by SPG faults [1,2]. Some methods have been proposed and applied to select faulty lines in RGDN. The existing faulty line selection methods can be categorized into two groups: active FLS (i.e., signal injection methods) ones and passive FLS ones [8,9] The former need additional signal injection devices and are limited by the capacity of voltage transformers, and the operation and maintenance is comparatively complex. FLS methods based transient information haveneural been have been proposed, such as high‐frequency component [13],onwavelet transform [14,15], proposed, such as high-frequency component [13], wavelet transform [14,15], neural network [16], network [16], expert system [17], extreme learning machine [18], zero‐sequence reactive power expert system extreme learning machine [18], etc.
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