• • • TEST & MEASUREMENT • • •
simulated about 10 years in the field at 30°C average ambient temperature. Phase 2 was performed in a controlled laboratory environment, as opposed to the field, in order to accurately assess the performance of the analytics service and to speed up the aging process for this small batch of meters. Similar to phase 1, the accuracy drift of the 19 devices was tracked to better than 0.1%, as shown in Figure 4, but now both the
Figure 3: Spread of drift of phase 2 devices]
has been conducted by VTT/MIKES, an independent testing house in Finland. Phase 1, where 19 working devices were removed from the field for accuracy testing, concluded in October 2018. Phase 2, where the same 19 devices were subjected to accelerated lifetime testing by VTT/MIKES, was concluded in November 2019. Testing with high accuracy test equipment was performed to find a baseline accuracy for all the devices prior to the trial and to validate accuracy drift in the devices. The results from the drift found by VTT/MIKES and analytics service after phase 2 is shown in Figure 3. The cloud-based analytics service is used in
conjunction with purpose-built evaluation devices installed on premise, in series with a primary meter. The evaluation devices shown in Figure 1 feature Analog Devices’ ADE9153B energy measurement IC, which includes mSure technology to enable advanced diagnostics. This way, the meter can pass raw diagnostic information to the analytics service, which performs analysis to provide alerts, observe trends, and give reports on the health of the meter. In a real deployment, utility companies can deploy meters based on the ADE9153B energy measurement IC and use the analytics service to seamlessly gain the benefits of mSure.
Field trial results In phase 1, the data from the cloud-based analytics service when compared to the reference measurements performed by VTT/MIKES shows that, for these 19 devices, the analytics service was able to track the accuracy drift to better than 0.1%. All 19 devices were grouped tightly and near 0%, showing minimal drift. In phase 2, the meters were allowed to age for eight months in an accelerated environment that
accuracy testing and the analytics service show an average negative drift of about –0.05%. As part of the laboratory experiments, one
meter was artificially aged to show the capability of the analytics to accurately track larger drifts. The artificial aging was performed by placing a resistor in parallel with the shunt to modify the shunt value. The shift caused by this aging was measured by VTT/MIKES to be –1.91%, while the analytics determined the accuracy shift of this meter to be –1.96%, or only a 0.05% difference. In conclusion, phase 1 of this field trial
showed that the analytics service is able to track the accuracy of mSure enabled devices deployed in the field very closely, within 0.1% but little meter drift was seen in that time. For phase 2, in a simulated 10 years in the field, the accuracy drift continued to be tracked at 0.1% as the accuracy testing and analytics showed the meters drifting in the negative direction. The field trial demonstrated the ability for mSure technology coupled with an analytics service to monitor meter drift with enough accuracy to be used in place of meter sample testing.
electricalengineeringmagazine.co.uk
ELECTRICAL ENGINEERING • MAY 2022 35
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