We all know the vision of a smarter energy grid: a high-tech, highly digitalised and data-led operation that enables a more resilient, sustainable and affordable energy system.

Then there’s the energy network in the UK to consider – the most aged in the developed world. “The reality is the grid was the first one built, and now it’s the oldest one around. It needs investment and update,” says David Elliman, global chief of software engineering at Zühlke.

The regulator recognises this too. Ofgem has announced an initial £8.9 billion investment in Britain’s high-voltage electricity network, with a further £1.3 billion in the offing ready to “power the biggest expansion of the electricity grid since the 1960s”. The draft settlement is the first step in an estimated £80 billion investment programme boosting electricity network capacity, “protecting UK households from the volatile international gas markets that caused the massive fluctuations in energy bills in recent years”, Ofgem said in July.

Meanwhile a lot of progress has been made in deployment of smart grid technology globally, spurred by a massive uptick in investment in the grid. More than a billion smart meters are now online across the world, 10 times the level in 2010. Twenty-five billion devices are predicted to be connected to the Internet of Things by 2030. And there are 320 million sensors out there on distribution networks. “The hardware layer looks impressive,” points out Elliman.

And yet, while investment in physical infrastructure is ramping up, the digital backbone of the grid, the systems, data and standards that make it truly smart, is still taking shape. Which begs the question, just how smart is the smart grid right now? How much more needs to be done to connect systems together and operate them intelligently?

And how far away is the vision of the smart grid from reality?

“The reality is we’ve got all these smart meters and sensors. Using them intelligently is a very different matter. Most utilities still replace equipment on fixed schedules with crews locating problems manually; it’s pretty rare to see predictive maintenance, or AI preventing failures in advance.”

One example of progress is Grid Code Modification 0139. This code, for ‘Enhanced Planning Data Exchange to Facilitate Whole System Planning’ should increase the scope and detail of planning data exchanged between NESO and the DNOs to help the transition to a smart, flexible energy system. The code is intended to improve the granularity and frequency of data to ensure DNOs and IDNOs can plan and operate more efficiently and cooperatively.

Such a change is “good, honest work to improve the quality of information exchanges between the networks”, says Steven Steer, principal data consultant at Zühlke. Among many hats he wears, Steer was responsible for authoring Ofgem’s standard for open data and digitalisation and overseeing the UK's Energy Data Taskforce. He explains that it took “six years to go from zero to finalisation of that grid code modification, and it’s a basic building block on which things like a proper self-healing grid would depend”.

He adds: “We’re years away from seeing that at scale; there are pockets of innovation that do things really well. But for scaled up, network-wide healing, and many types of analytics that would be desirable, we’re actually on an uncomfortably slow path.”