How AI technology is transforming the renewable energy industry
Recently, the Government announced a series of funding to support the clean energy movement with an accelerated focus on an artificial intelligence (AI) development plan. With significant value, renewable energy is likely to be the latest industry to benefit from the rise of AI.
With progress slowing in recent years, raising the level of automation in the renewables industry could be critical to realigning the UK on the path to achieving its net zero goals.
GreenJobs explores how AI can be integrated and benefit the renewables industry in the future.
Determining energy peak demands
At certain times of the day, the demand on the power grid changes considerably, but thanks to the advancement of AI, we can predict specific instances when energy demands fluctuate. By examining large sets of power usage data, AI can help the power grid manage demand efficiently by recognising when energy demand is especially high.
This same principle applies to the renewables industry. These AI-driven systems can determine when renewable energy is available and required, making integrating renewable energy into the grid simpler. Determining wind power can allow us to understand how much energy can be collected by turbines, which can also forecast how much will be available to the grid.
AI can enable professionals to explore relationships, find ways to mitigate grid failures and recognise how to re-distribute energy in the most effective ways.
Renewable energy technologies, like turbines and PV panels, are impacted by damages over time and require maintenance. Instead of waiting for an issue and a need for repair, companies are applying AI for predictive maintenance. This process involves placing sensors on generators, which assess data and predict when maintenance is needed. Considering how many generators in renewables, especially wind turbines, are located in remote regions, AI tools allow for strategic maintenance planning to keep downtime to a minimum.
Aside from predicting generator maintenance of wind turbines, AI can measure temperature and determine hot spots on large-scale solar systems, identifying cells that may be underperforming.
Managing and predicting weather patterns
Another application of AI in the renewables industry is its capacity to predict and then similar weather conditions. Renewable energy will always be available in terms of the sun, wind and rain, but the unpredictability is that it’s not always sunny, windy or rainy. Innovative weather simulators can predict future weather conditions, providing insight into our future energy potential. Aside from determining accurate weather reports, other simulators can display how city plans can impact airflows. This level of detail means industry professionals, like architects, can support the future of renewable energy by applying this knowledge to design cities in a way that works with the weather and renewable energy sources.
Delivering sustainable generators
While renewable energy is sustainable, developing sustainable technology, such as generators for the wind industry, is more challenging. Many renewable energy generators consist of rare earth materials, and their manufacturing process is also very energy-intensive.
AI is being applied to research new material options and assess their performance. This means thousands of manual tests can happen considerably quicker. AI can enable these generators to be recyclable once they reach their end of life, a critical element of sustainability.
The renewable energy industry is one sector benefiting from the progressive and transformative impact of AI. From enhancing generator efficiency to predicting energy demand, we’ve experienced how smart technology can strengthen our future use of renewable energy. Considering the escalating climate challenge, AI will inevitably be a critical part of the future of renewable energy.
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