Intelligent meters lie at the heart of a modern, reliable grid.
Utilities are facing unprecedented challenges in managing distribution networks, with distributed energy resources (DERs), such as electric vehicles and solar, changing load profiles and making demand difficult to predict.
To meet the needs of today’s rapidly changing market, utilities require intelligent meters that measure energy consumption at a faster rate and perform real-time data analytics at the edge of their distribution networks.
The days of simply measuring and reporting consumption are diminishing. Distributed intelligence (DI)-enabled meters are sophisticated network sensors capable of providing high-resolution data on upstream and downstream conditions, making them critical to grid modernisation.
Data boosting visibility
DI-enabled meters increase visibility by measuring detailed data that algorithms analyse to disaggregate the electrical consumption of appliances and equipment in customer homes and businesses.
With metrology sampling rates of up to 32kHz, these devices can precisely measure voltage and current waveforms, revealing the quality of the electricity supply, including information about voltage sags, swells, harmonics and other power-quality issues.
To reliably integrate new demand and generation from increasing DER uptake and to protect equipment in the process, utilities need visibility into the low-voltage circuits that only DI-enabled meters provide. For example, the meters on a single feeder or service transformer will be able to work in concert to calculate, monitor and even adjust net load, or let utilities know when equipment is at risk of failure.
Continuous monitoring
Because it’s difficult for humans to continuously analyse and monitor the high-resolution data that is required to provide real operational value, artificial intelligence (AI) is a promising technology for the energy industry.
Complex applications such as high impedance detection, meter bypass detection and advanced transformer load and voltage monitoring are made possible with machine-learning algorithms. High impedance detection, for instance, is an application that runs on a meter’s computing platform. The application alerts a worker in utility maintenance and operations if equipment begins trending towards failure – with no human intervention.
While AI provides a powerful tool to analyse problems like high impedance, other problems are suited to a more conventional processing strategy where grid-monitoring applications are run centrally in a back-office system or in the cloud.
Distributing the computing power and analytical intelligence into every meter has three distinct advantages:
- Faster control: locating analytics closer to the challenges they address reduces network latency and increases the speed with which systems can react to changing conditions
- Simplified data management: locating analytics in the meter greatly reduces the amount of data that needs to be transmitted, changing the paradigm from ‘big data’ to ‘right data’
- Customer engagement: DI-enabled meters are ideal for deploying the customised programs required to engage customers with valuable information about their DERs
Utility-focused solution
More than ever, utilities are looking to increase capacity to meet rising demand and manage the growing complexity of connected devices and two-way power flows. To do this, they require smart solutions that meet their specific needs.
Itron understands that when it comes time to invest in DI-enabled meters, utilities want to ensure they receive a strong return on investment and enough technological headroom for long-term growth.
In the development of every meter, Itron prioritises distributed intelligence, seamless and secure networking, ecosystem collaboration, operational efficiency and cost‑effectiveness.
With Itron’s DI-enabled meters, utilities can be sure to gain visibility to the meter and beyond to integrate DERs, increase customer engagement maintain reliability.
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