How AI is transforming the electricity grid – and why robot dogs could have a role to play

Artificial intelligence is already used across our energy networks, but in future the technology will play an even more pivotal role that verges on sci-fi

Artificial intelligence may have exploded in the public consciousness thanks to a new generation of attention-grabbing chatbots, but AI and machine learning have been with us for several years – and these more established models are already delivering significant returns.

Electricity grids and AI, for instance, are a match made in heaven. Grids are complicated, have vast numbers of inputs and outputs, require constant oversight and create huge quantities of data. Dealing with enormous numbers of variables and complex systems is one of the things AI does best – better, arguably, than pretending to be human.

Iberdrola, Europe’s largest utility company, which owns ScottishPower in the UK, has been using AI for more than 10 years to make predictions, optimise processes and detect patterns, which can be used to improve its operations. One example of this is providing customers with accurate estimates of outage times after incidents, via an app. Another is allowing engineers to plan ahead by telling them which grids or transformation centres will need partial replacements the following year, using myriad variables that predict possible issues based on historical data.

In a slightly more sci-fi vein, Avangrid, Iberdrola’s US subsidiary, announced last year that it had partnered with Levatas and Boston Dynamics to deploy a robot “dog” to improve substation inspections. The dog, nicknamed Spot, has sophisticated imaging and thermal technology and uses AI to detect damaged equipment. Automated inspections will take place more frequently and the result will be greater reliability for customers.

Maximising renewables output

But AI isn’t just about making grids more operationally efficient. It is also helping to make energy more clean. Renewable sources of energy such as wind and solar are by their nature variable, but AI can help operators maximise the electricity they produce, reduce wasted energy and limit the need for fossil fuels as back-up sources. “By predicting when and where energy will be needed, AI can help avoid outages and cut down on wasted power,” says Justin Bates, co-founder of ESGmark, an organisation that promotes and recognises environmental, social and governance standards in business.

For companies such as Iberdrola, this begins in the design phase. It might start with AI-driven models finding the optimum location of a wind turbine, based on years of meteorological data. It could then go into operations and maintenance. This may include using algorithms to predict maintenance issues before they occur, or anticipating wind or solar production for each hour of the day. Knowing what is being produced and where can help balance the grid, either by shifting energy around, by releasing stored energy (such as pumped hydro) or switching on back-up energy (which may come from fuels such as gas) where needed as a last resort.

Improved energy storage solutions

Back-up fossil fuel capacity should be needed less in the future thanks to more innovative and dependable renewable-energy storage solutions – and, again, AI is playing a crucial role in these. Last year, Iberdrola partnered with Multiverse Computing, a global leader in quantum computing solutions, to deliver a pilot project in northern Spain to optimise the installation of grid-scale batteries. Multiverse’s solution uses quantum and quantum-inspired algorithms to select the optimal number, type and locations of batteries on the network – thereby reducing the costs of adding batteries to the grid and improving network performance.

Similarly, as batteries become an increasingly important part of the grid, AI could help enlist the batteries in electric vehicles. The latter could potentially form a part of the grid’s battery capacity – the UK’s cars famously spend 96% of their time parked. AI could help balance these thousands of connections.

AI can also allow grids to do more with what they already have. “Innovative grid technologies, including those based on AI, allow us to transport more electricity through our existing electricity infrastructure, by improving our understanding of the real-time conditions of our increasingly complex electricity networks,” says Layla Sawyer, secretary general of CurrENT, which represents grid technology providers in Europe. “This includes the effect of weather conditions, dynamic energy production and consumption, and many other factors that impact grid operators.”

Keeping customers informed

At the other end of the energy supply network, AI can improve the way energy companies interact with their customers. This entails sharing information on topics ranging from outages to expected bills, but also helping customers to conserve energy. “AI can help energy companies to connect with customers in a more meaningful way, encouraging smarter energy use that benefits everyone and supports ESG principles by creating a fairer, cleaner energy system we can trust,” says Bates.

Finally, AI can even help wildlife. In the future, AI modelling will be able to analyse bird flight paths and recommend renewable sites that reduce ecological concerns, while Iberdrola’s existing AI power systems can detect birds and stop specific turbines if required.

It’s modelling like this that really encapsulates the benefits of AI to the grid. While the technology has already been used for a number of years to improve existing systems, in future, it will increasingly be embedded in the planning stage of large-scale infrastructure projects and integral to their operation. As Bates points out: “AI is helping to transform our energy grids, making them smarter, more reliable, and ready to handle cleaner energy.”