A Smart Sensing Method for Real- Time Monitoring of Low Voltage Series-Arc-Fault
This paper proposes a smart sensing method for real-time monitoring of low voltage series arc fault. It is based on the wavelet coefficient mean-difference algorithm and the four spikes appearing within two fundamental periods criterion with adaptive threshold. The method also uses the hard thresholding wavelet denoising with the universal threshold. An arc fault factor and a load adaptation factor are introduced and combined with a correction factor, so allowing the selection of the adaptive threshold in real-time and the series arc fault detection.
Fractal Dimension Logarithmic Differences Method for Low Voltage Series Arc Fault Detection
Series arc faults introduce singularities in the current signal and changes over time. Fractal dimension can be used to characterize the dynamic behaviour of the current signal by providing a degree of signal chaos. This measure of irregularity exhibits changes in signal behaviour that can suitably be used as a basis for series arc fault detection. In this paper, an efficient low voltage series arc fault detection method based on the logarithmic differences of the estimate of the fractal dimension of the current signal using the multiresolution length-based method is presented. The discrete wavelet transform and the hard thresholding denoising with the universal threshold are also used. Exp…
On the Non-Intrusive Load Monitoring in dwellings: a feasibility perspective
The oncoming modernization process of the power grids, driven above all by decarbonisation objectives and the continuous improvement of digital technologies, is encouraging active participation in the electricity market by consumers through the Demand-Response mechanism. From this perspective, the introduction of smart meters and energy consumption monitoring devices plays a fundamental role, being able to give benefits to consumers, suppliers and the electricity grid itself. This paper proposes a supervised method of non-intrusive load monitoring (NILM) based on the recognition of patterns in the time domain with the Dynamic Time Warping algorithm which is suitable for low-cost smart meter…