How will AI inform our changing energy market?

While more organisations are beginning to adopt artificial intelligence (AI), we’re really yet to realise its full potential – but we can already see that for the energy industry, AI could bring some significant benefits.

Every step we make towards a greener economy is a positive one, but the journey isn’t without its challenges. Energy supply is becoming harder to predict due to the increase in renewables and distributed generation, for example, making it increasingly difficult for the National Grid to balance supply and demand. The grid needs to become smarter to meet the requirements of our changing energy system – and AI is likely to be a key factor in making the grid more intelligent.

Here are just a few of the ways that AI can help us to move towards a new energy future:

Make more precise predictions

The National Grid is already looking into how AI can be embedded into our electricity system – in March 2017, they announced that they would be working with Google-owned AI company, DeepMind. A key focus of this project is exploring how National Grid could use DeepMind technology to process data on everything from weather forecasts to internet searches, in a bid to develop more accurate predictive models for electricity supply and demand.

National Grid have stated that they’re hoping that AI technology could help them to improve their performance, make the most of renewable energy and save electricity customers money. Simply by implementing neural networks and machine learning, they are aiming to cut the national energy bill by 10%.

Become more energy efficient

Another one of the benefits the National Grid hope to get from using AI is to make the UK grid more efficient. Our electricity system is so large that it’s inevitable that inefficiencies will arise at different points, but with AI we could significantly reduce lost energy.

Google has already successfully used it’s DeepMind technology to cut electricity usage at their data centre by 15%, which it achieved by training a neural network to predict future cooling requirements within the data centres. They are now hoping to see similar success on a much larger scale through the National Grid.

Manage distributed generation

Our energy is increasingly sourced from distributed generation (DG), with installation of solar panels, small-scale generators and CHP and natural gas generators becoming more widespread. DG makes it more difficult for National Grid to predict capacity levels, but AI could make this task much easier.

It’s AI’s ability to analyse massive datasets that could really help National Grid when it comes to distributed generation. AI software can process data from DG sources across the UK and provide the National Grid with a detailed view of when and where capacity is available. It could also be used to enable distributed storage assets to participate in demand response, as AI solutions with machine learning capabilities could analyse data from each individual asset and select the optimal assets to call upon in different scenarios, creating a more intelligent grid.

A smarter energy future

It’s not just the National Grid that will be utilising AI in the near future – our research for our Future Utilities Manager report revealed that AI will become a key part of energy managers’ roles by 2030. You can download the full report here, and if you’d like to find out more from one of our experts, give us a call on 08451 46 36 26 or email enquiries@inenco.com.

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