Detection Methods for Current Signals Causing Errors in Static Electricity Meters

Abstract

In recent years, the shift to Distributed Generation (DG) and the use of smarter domestic appliances has led to an increasing integration of power electronics (active infeed converters, power drive systems etc.) at the household level. However, the use of more power electronics results in the generation of highly distorted currents entering the distribution grid. Previous research shows that such current waveforms can cause large errors in static electricity meters. Thus, there is an imperative need to study the characteristics of these current waveforms and their impact on meter readings by performing extended measurements in households. Since it is not practical to store all the high granularity waveform data of such measurements, suitable detection methods and trigger levels need to be defined to only capture the potentially problematic current waveforms. In this paper, signal processing techniques (differentiation, Short Time Fourier Transform and Wavelet Transform) are applied to current signals in order to extract features suitable for use as a trigger. Results show that the Discrete Wavelet Transform and the filter with derivative method give the most promising results and work reliably even for very noisy signals.

Towards improved standardization of electricity meter testing

“…This validation shows that the testbed is suitable for testing electricity meters using any relevant waveform, including future standardized test waveforms and waveforms that might be useful for scientific research such as wavelet decomposition or other analysis of test signals [6].…”

“…An on-site meter was developed to record potentially harmful waveforms and to serve as a benchmark meter in case of disputes between end users and utilities. When recording waveforms at high sampling rate, a trigger mechanism should be used to avoid an overflow of measurement data [6]. The onsite meter developed uses threshold settings for crest factor and dI/dt to trigger waveform capturing.…”

On-Site Waveform Survey in LV Distribution Network using a Photovoltaic Installation

“…As indicator wavelet coefficient 4 is used, representing the frequency range from 31.25 kHz to 62.5 kHz. This DWT trigger was shown to be a strong indicator for the type of signals to be triggered in this research [14]. Furthermore, a snapshots is made every ten minutes (free-run).…”

“…[13] and wavelets [14]. The wavelet trigger is a discrete wavelet transform (DWT) using the Daubecchies wavelet with two filter coefficients (db2) as mother wavelet.…”

A Testbed for Static Electricity Meter Testing with Conducted EMI

“…Instead, load current waveforms from different mass-market electrical goods can be captured and categorized according to the relevant key parameters found so far to be responsible for the observed meter errors, i.e., high rate of change of current, peak amplitude and crest factor. Analysis of alternative key parameters, for example based on wavelets or short-time Fourier transforms, is ongoing [13]. For future type testing, from these categorized waveforms representative signals can be selected and, if necessary, modified.…”