0000000000860039

AUTHOR

Claudio Fontana

0000-0001-9361-4252

showing 3 related works from this author

A Smart Sensing Method for Real- Time Monitoring of Low Voltage Series-Arc-Fault

2020

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.

Series arc faultSeries (mathematics)Computer science020208 electrical & electronic engineeringArc-fault circuit interrupter02 engineering and technologyArc fault current interrupter (AFCI)ThresholdingSettore ING-IND/31 - ElettrotecnicaWavelet0202 electrical engineering electronic engineering information engineeringElectronic engineeringWavelet denoisingSettore ING-INF/07 - Misure Elettriche E ElettronicheLow voltagearc fault detection devices (AFDD)2020 IEEE 20th Mediterranean Electrotechnical Conference ( MELECON)
researchProduct

Fractal Dimension Logarithmic Differences Method for Low Voltage Series Arc Fault Detection

2021

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…

Discrete wavelet transformFractal Dimension (FD)Multiresolution Length-based Method (MRL)Computer scienceArc-fault circuit interrupterFractal dimensionSignalFault detection and isolationElectric arcDiscrete Wavelet Transform (DWT)series arc signal analysisFractalWaveletArc Fault Detection Device (AFDD)Arc Fault Current Interrupter (AFCI)Algorithm2021 5th International Conference on Smart Grid and Smart Cities (ICSGSC)
researchProduct

On the Non-Intrusive Load Monitoring in dwellings: a feasibility perspective

2021

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…

Dynamic time warpingComputer scienceProcess (engineering)Energy consumptionHeuristic algorithmsPower system dynamicsEuropeLow-carbon economyElectricity supply industrySmart meterssmart gridnon-intrusive load monitoring (NILM)dynamic time warping (DTW)Electricity marketMetering modeTime domainEnergy consumptionLow-carbon economyIndustrial engineeringPower (physics)2021 IEEE International Conference on Environment and Electrical Engineering and 2021 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe)
researchProduct