Electricity networks are becoming increasingly dependent on digital field devices whose performance must be assessed over the full span of their service life. Among these assets, smart meters are particularly important, as their degradation can compromise data availability, increase maintenance effort, and ultimately affect the quality of grid operation.

Traditional asset replacement strategies, typically based on age or fixed maintenance intervals, are often too general to reflect the real condition and risk profile of such equipment. As grids become more digitalised, there is a growing need for more accurate and data-driven approaches to asset management.

A data-driven solution within OPENTUNITY

To address this need, ICCS has developed, within the OPENTUNITY project, a Long-Term Asset Management Tool focused on the reliability assessment of smart meters.

The solution leverages historical data from Advanced Metering Infrastructure

 systems to model how assets age under real operating conditions. Based on this information, it estimates the probability of failure for different meter populations, providing system operators with a more realistic understanding of asset behaviour over time.

A key outcome of this analysis is the generation of End-of-Life curves for different types of smart meters. These curves help operators identify when specific models are expected to enter higher-risk phases, supporting more informed and timely decision-making.

From population trends to individual risk detection

In addition to long-term statistical analysis, the tool incorporates machine learning techniques applied to operational measurements. This allows the identification of individual devices that may present an increased risk of failure, even if they are not yet part of a broader trend.

By combining population-level insights with device-specific analysis, the tool enables early detection of potential issues and helps prevent failures before they become widespread.

Supporting decision-making through an intuitive interface

The Long-Term Asset Management Tool is supported by a user-friendly interface designed to facilitate its integration into daily operations. Through this platform, users can upload meter and substation data, review key performance indicators, and explore reliability trends across their asset base.

Operators can also compare the performance of different meter models, estimate expected failures over selected time horizons, and identify critical devices that require priority attention. The inclusion of geographic visualisation further supports this process, offering a clearer view of how risks are distributed across the network.

Towards proactive and efficient maintenance strategies

By linking statistical reliability analysis with data-driven risk detection, the tool provides utilities with a solid basis for medium- and long-term planning. It supports a transition from reactive maintenance practices to a more proactive and targeted approach, where decisions are based on actual asset condition rather than predefined schedules.

This shift enables better allocation of maintenance resources, reduces operational costs, and improves the overall reliability of the digital infrastructure that underpins modern power systems.

Strengthening the foundations of future power systems

As electricity networks continue to evolve, ensuring the reliability of digital assets such as smart meters becomes increasingly critical. The Long-Term Asset Management Tool developed within OPENTUNITY represents an important step in this direction, providing system operators with the tools they need to manage complexity and enhance grid resilience.