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

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Static energy meters have shown errors beyond the standards due to conducted electromagnetic interference of pulsed currents. This was observed in several case studies and confirmed by laboratory experiments, which showed errors up to 2675%. The extent of this interference case is unknown, because there is limited information about the waveforms occurring in the real on-site scenarios. This article aims to detect critical waveforms in on-site surveyed data that have similar characteristics as the pulses that resulted in metering errors. The time-domain parameters of the laboratory experiments that show static energy meter interference are compared to the on-site waveform data using an interpolation based on an inverse weighting distance function. Using this approach, the waveform characteristics are compared, and an error is estimated. This approach was satisfactorily validated using data from validation experiments that shows a correct estimation of the actual error according to the permissible limits for energy metering for all validation indices. The performed on-site surveys show the existence of nonlinear waveforms. During the survey of three sites for ten days, 19 531 waveforms were captured, of which 14 487 indicate large nonlinearities and 379 are estimated to produce metering errors up to 925%. Index Terms-Electromagnetic interference (EMI), nonlinear waveforms, on-site survey, static energy meters, time domain. I. INTRODUCTIONS TATIC energy meters measure the energy consumption in residential situations for billing purposes. In previous research, major interference errors of a number of specimens of static energy meters are shown in diverse test conditions. The interference was observed due to harmonic disturbances [1], photovoltaic (PV) installations and power drive systems [2]-[4],

“…Site 1 uses a three-phase system, while sites 2 and 3 use a single-phase system. Some preliminary results of sites 1 and 2 were already published in [17] and [18].…”

Section: Methods For On-site Surveymentioning

confidence: 99%

Section: B Measurement Settingsmentioning

confidence: 99%

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confidence: 99%

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Estimation of Static Energy Meter Interference in Waveforms Obtained in On-Site Scenarios

Have

Azpúrua²,

Hartman

et al. 2022

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“…Critics argued that the distortions used in [15] are rather extreme and are artificially generated in the laboratory and do not represent a realistic situation in typical households using CE-marked equipment. Recently, however, highly disruptive waveforms have been recorded caused by other household appliances [18], including a water pump [19] and in real onsite situations by electric vehicle (EV) chargers [20] or photovoltaic (PV) installations [21] that are beyond the present standardization and require time domain investigation [22].…”

Section: Introductionmentioning

confidence: 99%

EMC Testing of Electricity Meters Using Real-World and Artificial Current Waveforms

Brom

Leeuwen

Marais

et al. 2021

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In 2015, the energy measurement of some static electricity meters was found to be sensitive to specific conducted electromagnetic disturbances with very fast current changes caused by highly nonlinear loads, leading to meter errors up to several hundred percent. This article describes new results on the electromagnetic compatibility (EMC) of 16 different meters from all over Europe when exposed to real-world disturbance signals. Those test signals were obtained from household appliances and onsite measurements at metered supply points all over Europe. The results show that also the interference signals recorded onsite can cause measurement errors as large as several hundred percent, even for meters that pass the present EMC standards. This unambiguously demonstrates that the present immunity testing standards do not cover the most disturbing conducted interference occurring in present daily-life situations due to the increased use of nonlinear electronics. Furthermore, to enable the adoption of potential new test waveforms in future standards for electricity meter testing, artificial test waveforms were constructed based on real-world waveforms using a piece-wise linear model. These artificial test waveforms were demonstrated to cause meter errors similar to those caused by the original real-life waveforms they are representing, showing that they are suitable candidates for use in improved standardization of electricity meter testing.

“…Furthermore, in the framework of the MeterEMI project [20], surveys are performed in modern LV distribution networks. Preliminary results are shown including networks with electric vehicle (EV) charging stations [21], and PV installations [22]. This resulted in a vast repository of datasets comprising on-site current waveform measurements.…”

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confidence: 99%

Waveform Model to Characterize Time-Domain Pulses Resulting in EMI on Static Energy Meters

Have¹,

Azpúrua²,

Hartman³

et al. 2021

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This article presents a time-domain waveform model developed to characterize pulsed, nonlinear, current waveforms resulting in electromagnetic interference on static energy meters. The waveform model is calculated by fitting the sampled waveform data into a linear piece-wise function through a process that involves applying algorithms of pulse extraction, change-point detection, and redundancy elimination. The model is applied to data from laboratory experiments that have indicated critical current waveforms resulting in electromagnetic interference problems with static meters. Afterwards, the parameters of the modeled waveforms are calculated in order to correlate them to metering errors. The most relevant parameters that are correlated to significant errors are the maximum slope, crest factor, pulse duration, and charge. The waveform model provides an accurate description of the complex nonlinear waveforms through simplified analytical expressions that reproduce the significant features of the interfering waveforms. This waveform modeling approach could be used to standardize the artificial test signals that are representative of realistic devices and scenarios.