A new simple and effective algorithm of arcing fault detection in distribution networks with the application of a wavelet transform technique is presented in this paper. The protection algorithm developed observes the phase displacement between wavelet coefficients calculated for zero-sequence voltage and current signals at a chosen high-level frequency. The final decision in regards to feeder switching off (or alarm issuing) is met either with a deterministic logic scheme or with the use of a neural net trained especially for that purpose. The developed wavelet-based high-impedance fault (HIF) detector has been tested with Electromagnetic Transients Program-Alternative Transients Program (ATP)-generated signals, exhibiting better performance than traditionally used algorithms and methods. The protection method proposed may be used for HIF detection independent of the network neutral-point grounding mode. The scheme proved to be robust against transients generated during normal events such as feeder energizing and de-energizing as well as capacitor bank switching

Application of two new ANN-based algorithms for arcing high impedance fault (HIF) detection in multigrounded medium-voltage (MV) distribution networks is presented in this paper. The paper provides an evaluation of two new structures of artificial neural networks (ANNs) that may be used for reliable HIF detection in multigrounded as well as isolated, compensated, and grounded via small resistance distribution grids. The results obtained by use of both neural nets are presented. The performance was tested using data obtained from staged HIFs in real MV network as well as from electromagnetic transients program-alternative transients program simulations. A small number of necessary neurons in developed ANNs, short measuring sliding data window, and easy interpretation of obtained output signals are the main advantages of the proposed approach. Satisfactory results of ANN performance were observed for all examined HIF cases in which the ground fault current was greater than 16 A. The selected ANNs of best performance show high reliability and immunity to transients resulting from switching operations in protected feeders and from capacitor bank switching.

If a current transformer (CT) saturates while transforming the heavy primary current, in each period, there are sections when the magnetic core is unsaturated and transformation is correct, and when it is saturated, it causes enormous errors. The key to correct the errors is to detect instants of saturation and moments when the saturation ends. This paper presents simple and efficient methods of doing that. In addition, it shows the way how to predict up to three samples after saturation with the acceptable degree of accuracy, thus artificially expanding the unsaturated section. It may substantially facilitate operation of protective devices. The ultimate solution of the problem is to estimate the values of the fundamental frequency component amplitude and the decaying DC component in each period. This paper presents the method of doing that on the ground of four consecutive samples taken during the unsaturated section. If the primary current consists of the fundamental and DC exponential components only, the accuracy of the method is excellent. Neglecting contamination of the current signal with harmonics and noise, it is possible to reconstruct the CT primary current based on the measured values of fundamental and DC components.

A new algorithm of power system frequency estimation is presented. The algorithm applies orthogonal signal components obtained with use of two orthogonal FIR filters. The essential property of the algorithm presented is its outstanding immunity to both signal orthogonal component magnitudes and FIR filter gains variations which ensures 1.5 mHz accuracy of estimation over typical (±2 Hz) range of measured frequency deviation. The results of the algorithm simulation tests using the EMTP software package are also included. It was confirmed that the algorithm dynamics are good enough to track power system frequency even under transient conditions.