CNAIM: is the UK's risk-based maintenance model on its way into the Swedish grid?

CNAIM comes up more and more often in our conversations with customers. It’s a way of prioritising maintenance based on what a component would actually cost to lose, not simply how old it is. Internationally, the idea is far from new. In the UK, a framework like this has been mandatory for over a decade, under the name CNAIM: the Common Network Asset Indices Methodology.

And it’s not just industry talk: one of Sweden’s largest grid companies, Vattenfall Eldistribution, has spent the past year evaluating how well CNAIM’s calculated probabilities of failure match actual fault statistics in the Swedish network, aiming to propose adaptations for Swedish conditions. In other words, the UK model is no longer just an academic reference in Swedish reports. It has already begun being tested against real Swedish operational data.

We’ve seen this firsthand. Gomero has been part of a project evaluating CNAIM together with a Swedish grid company, using real data from one of our own installations as the basis.

CNAIM was developed by the UK’s distribution network operators together with the regulator Ofgem, and from 2015 became part of network operators’ licence conditions. It’s a requirement, not a choice. It gives every UK network operator a common way of assessing 25 different asset classes, from transformers and switchgear to cables and overhead lines.

At its core, CNAIM rests on two calculations per asset:

• Probability of Failure: how likely is it that this specific component will fail, given its age, condition, loading, and other factors?
• Consequence of Failure: what would it cost, in financial, reliability, safety, and environmental terms, if it did?

Together, these produce a monetised risk value per asset. That makes it possible to compare a transformer in one region with a cable in another on the same scale, and direct the maintenance and investment budget to where it actually makes the biggest difference, rather than following a schedule set twenty years ago.

CNAIM is no longer an isolated UK phenomenon. The framework has already been adapted for several other countries, including Denmark. The pattern is the same everywhere: a grid company or regulator finds that scheduled maintenance is neither cost-effective nor particularly good at predicting failures, and opts for a proven, transparent model instead of building one from scratch.

The same pressure exists in Sweden. The Swedish Energy Markets Inspectorate has proposed a more total-cost-focused regulatory model (TOTEX), which makes it more financially attractive for grid companies to invest in condition monitoring and risk-based decisions rather than simply minimising short-term spending. A clear, auditable framework like CNAIM fits well into that context: both internally, to prioritise correctly, and externally, to justify decisions to the regulator.

Here we want to be honest about something that’s easy to overlook in the discussion: a risk model is only as good as the data feeding it.

At its core, CNAIM can run on age alone. The methodology is built to work even without complete condition data. But the value of a risk-based prioritisation grows considerably with the quality of that input data: an estimate based on age alone gives a blunt picture, while real, up-to-date information about each component’s condition makes both the risk assessment and the decisions it informs considerably sharper.

That’s precisely the foundation we build on at Gomero. You don’t need to replace your existing systems to get started. We add the intelligence layer that lets methods like CNAIM actually deliver in practice: reliable, continuous data on the condition of every substation, gathered in one place and ready to serve as the basis for risk-based decisions.

We don’t know whether CNAIM will end up being the model widely adopted in Sweden, or whether the industry lands on its own variant. But the direction is hard to mistake: from schedule to risk, from assumptions to data. It’s a conversation we’re happy to continue, wherever you are on that journey.