Single Line to Ground Fault Detection in a Non-Effectively Grounded Distribution Network

TLDR: Algorithms that combine complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) and Hilbert transform to construct a multi-criteria comprehensive voting method that has higher accuracy and a faster calculation speed are proposed.

Abstract: In the event of a single line to ground (SLG) fault in a non-effectively grounded distribution network, the faulted current is weak (only a few amperes or less) and the existing devices cannot accurately judge the faulted feeder. In this paper, we proposed algorithms that combine complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) and Hilbert transform to construct a multi-criteria comprehensive voting method. First, CEEMDAN algorithm is used to decompose the zero-sequence current to obtain the IMF1 (the first intrinsic mode function) component and the Hilbert transform is used to calculate the instantaneous amplitude and instantaneous phase. Then, according to the three largest instantaneous amplitudes information, we constructed the characteristic instantaneous phase, characteristic instantaneous energy relative entropy and characteristic instantaneous zero sequence current polarity criteria from the phase, energy and polarity, respectively. Finally, we proposed a comprehensive voting method, which is specifically shown as follows: when two or more criteria show that one feeder or the bus has an SLG fault, it is voted that the feeder or the bus has an SLG fault. In contrast, if the judgment results of the three criteria are inconsistent, then we would return to recalculation and then vote. Compared with existing method, simulation tests and field experiments show that the method proposed in this paper has higher accuracy and a faster calculation speed.