How modern technology is shaking up the alternative energy sector

It’s clear that renewable energy is a key area of focus for our new government, but could advancements within the AI sphere of technology help us achieve our net zero target for greenhouse gas emissions by the year 2050?

There are various use cases for AI in the renewables sector. We spoke with Charlotte Enright, Renewables Specialist at commercial finance experts Anglo Scottish Finance, to discuss how AI is being used – and could continue to be used – to enhance the renewables sector.

Predicting the future of energy demand

Strain on the power grid is becoming a concern of the past, thanks in part to AI’s influence. As Enright explains: “Machine learning has enabled us to accurately predict surges or changes in energy demand and respond accordingly.

“We can predict the most likely times for an increase in energy demand – responding to thousands across the country popping the kettle on during an advert break for the popular TV programme of the moment. But with the ongoing AI advances, we can now predict much more than a quick cuppa break.”

AI can help the power grid manage demand by providing a better understanding of how and when we’re using the most energy. It does so by meticulously analysing huge amounts of power usage data. This same principle applies to renewable energy, with AI-powered systems able to understand, analyse and predict when renewable energy is available and when it’s most likely to be required.

“This enhances the reliability of this form of energy,” Enright comments. “Meaning it can be used to power more homes, businesses and organisations across the UK.”

Integrating renewable energy into the grid is also made simpler with the introduction of AI. Predicting wind power can help us to understand how much energy can be collected by the new wind turbines promised by Starmer’s government, forecasting how much of it will be available to the grid.

AI is used to correlate trends and better forecast demand. As Karen Panetta, an Institute of Electrical and Electronics Engineers’ fellow, adds: “This predictive technology can help us mitigate failures in the grid and understand how to re-distribute energy efficiently.”

Reliable energy generators

AI can also help us enhance the reliability of renewable energy generators. These generators, like wind turbines and solar panels, are prone to wear and tear and require regular, professional maintenance. But rather than waiting for a fault to occur to fix generators, businesses are now using AI for predictive maintenance.

Enright explains: “Sensors are placed on the generators, analysing data and predicting when maintenance will need to be performed. This is a brilliant advancement, as many of these generators, particularly wine turbines, are situated in remote areas.

“This AI-focused approach allows for the strategic scheduling of maintenance, increasing reliability and minimising downtime.”

This same AI technology can also be harnessed to monitor temperature, identifying potential issues before the begin to cause problems. As Enright explains: “AI can be used to locate hot spots on large-scale solar panels, which can indicate malfunctioning cells before they cease to work altogether.

“Maintenance can then be performed on the panel as soon as possible. The identified cells can also be re-angled to optimise the power captured, thanks to AI-powered light pattern predictions.”

Simulated weather conditions

AI can also go beyond mere predictions, actually simulating probable future weather conditions. “The unreliability of renewable energy often comes from the unpredictability of our British weather,” Enright explains.

“We cannot count on the fact that it will be sunny, rainy or windy at the times required. Also, too much or too little of these specific conditions can have a knock-on effect on organic materials, such as the growth of grass and plants.

“However, intelligent weather simulators can now predict future weather conditions, giving us insight into our future energy-capture potential.”

Going beyond simple weather reports and forecasts, these AI tools can provide further, detailed insights, even highlighting how the layout of a city can impact airflow.

These insights provide benefits for the building sector, helping architects to support the future of renewable energy by designing buildings and cities that work with the weather and renewable energy sources identified for a particular area, rather than against them.

The question of sustainability

Renewable energy is often talked about in relation to the issue of climate change, so we often think of these energy sources as fully sustainable. Unfortunately, this is not always the case.

The majority of renewable energy generators are crafted from rare earth materials, using up limited, valuable resources. The manufacturing process of these generators themselves is also highly energy-intensive.

However, there is hope. Enright explains: “AI technology is being used to speed up trials of new materials and their performance. This means thousands of manual tests can be condensed into a more manageable number.

“This technology can also support designers and manufacturers in ensuring that renewable generators are recyclable once they reach the end of their lifecycle, making the whole process more sustainable.”

The transformative effects of AI have multiple applications across the renewable energy sector. We’re seeing this smart technology improve the reliability and usage opportunities of renewable energy, predicting energy demand and adapting accordingly. Considering the importance of the fight against climate change, this might be one of the most important uses of AI technology to date.