Power Quality Measurement Capabilities of “Smart” Energy Meters

Abstract

Power quality measurement integrated in energy meters are presented as a potential benefit by some manufacturers. The Norwegian regulator has considered making minimum requirements for energy meters to include registration of interruptions. SINTEF Energy Research has performed tests on energy meters with power quality measurement capabilities. These tests include the ability to detect interruptions, supply voltage variations, voltage dips, among others. Results presented in this paper show large differences in capabilities for power quality measurement of 'smart' energy meters. The results also show that the power quality measurements are not according to international standards for such measurements like EN50160 [1], IEC 61000-4-30 [2] and others.

A Novel Method for Single and Simultaneous Fault Location in Distribution Networks

“…1) Performance With Noisy Measured Data: Smart feeder meters measure the pre-and during-fault voltages with between 0.1 to 0.5% accuracy [37], [39]. Load and temperature fluctuations significantly affect smart meter accuracy [38].…”

Low Voltage Zones to Support Fault Location in Distribution Systems With Smart Meters

“…Besides these two features, another important issue is the minimum operating voltage because if this value is too high, the meters cannot help in the fault location process with low fault resistances. In [18], an investigation of the measurement capability of five smart meters brands is presented. It shows that smart meters available in the market are capable of measuring voltage magnitude and/or reporting outages.…”

“…It shows that smart meters available in the market are capable of measuring voltage magnitude and/or reporting outages. More details about the tests results can be found in Table I [18].…”

“…Typically, substation measurements are more accurate than measurements from smart meters, which accuracy class ranges from ±0.1% to ±0.5% [18], [22]. However, in order to achieve a conservative assessment of the method performance, the following standard deviation values are used to define the density function of the errors.…”

Fault Location in Distribution Networks by Compressive Sensing

“…Specifically, the numbers of faulted buses with less than 200meter error for noises generated by N(0,1%) are not that much different from those obtained for noises generated by N(0,0.5%). Although the accuracy class of smart feeder meters usually falls in a range of 0.1-0.5% [28], we increase the noise intensity to explore the upper bound on the noise level. Since ℓ s 1 can handle small dense noises, when the measured voltage magnitudes are corrupted by more than 1% noise level, the number of faulted buses estimated with more than 400m error becomes significant.…”