Online Estimation of Short-Circuit Fault Level in Active Distribution Network

Abstract

The potential short-circuit current in active distribution network features time-variance with the increasing distributed generations. This feature makes the online estimation of fault level necessary. In this paper, a novel online estimation method is proposed to be implemented by either phasor measurement unit (PMU) or the measurements from protection relays. The equivalent circuit of the radial distribution network with distributed generators (DGs), e.g., wind turbines and photovoltaic cells, is derived with necessary simplifications. The natural disturbances downstream are used to evaluate the parameters of the equivalent circuit so that the potential fault level can be estimated in advance of the actual fault occurrence. A fuzzy logic identifier is presented to rank the confidence of the measurements incurred by the disturbance and to distinguish the qualified disturbance to launch the estimation. The mechanism based on multi-measurements and confidence indices was applied, to improve the accuracy. A typical distribution network in the United Kingdom (UK) with DGs was taken, as an example, to validate the proposed method under various load fluctuation. The results confirm the effectiveness of the proposed method, which is suitable for online estimation of short-circuit fault level in active distribution networks.

Singular Signal Measurement Based on Bidirectional Recursive Complex-Valued Wavelet Algorithm

“…It reflects the distance to the fault by the decrease in impedance. Decide on the protection action: in order to more accurately distinguish between normal operating conditions and fault (or abnormal) conditions, there are no or few fault conditions during normal operation but there are large electrical quantities, such as negative sequence or zero sequence current, voltage, and power judgment: the use of power system fault protection is not limited to electrical quantities, but also other physical quantities, such as a large amount of gas and an increase in oil flow rate or oil pressure caused by a fault in the transformer tank [11][12][13][14][15]. e fault diagnosis is shown in Figure 1.…”