Researching the Role of AI in Renewable Energy Again: Part 1, Predicting Patterns and Optimising Energy Production

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Researching the Role of AI in Renewable Energy Again: Part 1, Predicting Patterns and Optimising Energy Production

Back to doing the thing I loved most in the world again.

Why Have AI in Renewable Energy

As always, AI in renewable energy is so badly needed due to one main reason: demand. Various places in the renewable energy industry where AI is needed are:
  • The generation of renewable energy
  • The stabilisation of the grid (very important one!!!)
  • The optimisation of energy storage (including, think, EVs, batteries, and so on)
  • And the utilisation of renewable energy assets - one of my favourite ones! Such as planning maintenance works and being more intelligent with them using AI to make smart planning decisions based on information such as resources available and planned works, as well as integrating these with data based on predicted faults - I am really blessed to be working in a team who are doing some really interesting stuff around this at the moment - with water

Predicting Patterns

Due to the unpredictability of the weather, the ...seasonality... of seasons (the changeability), AI can lend some predictability to the renewable energy generation process thanks to its models. 

Data that AI can take into account includes
  • past consumption data
  • altitude
  • major upcoming events
  • weather forecasts
  • predicted supply and demand
  • sensor data
  • forecasting of energy production for unpredictable power sources such as solar and wind
It can also help us to make real-time decisions around whether to power up certain power stations or not, saving us so much money on unused generated electricity supply, stopping the grid from being overloaded, and of course being good for the planet as well, of course, as it stops us from generating excess electricity (especially as the grid is made up of both sustainable and non-sustainable power plants). The more energy is saved the better. But we can also use AI to target the production of our renewable energy better. We can direct our resourced in certain, improved, ways.

Targeting Energy Production Better

It's simple and it's pretty obvious and it doesn't need AI - but AI can help us to do it better. If wind is expected to rise, we turn on more wind energy infrastructures and we rely more on those. 

Completely obvious. 

But with AI we can bring in more predictive data into the model, we can optimise how we store any of this excess energy - whether or not the resources are available or not for storage - and we can target the usage of this energy to optimum consumers.

As well as reducing consumption of non-renewable energy resources, and reducing energy wastage (it gets to me so much! energy waste), this kind of work increases our energy security - when we are more reliant on our own energy supplies, we are less dependent on those around us - and one of the biggest barriers to the uptake of renewable energy resources and the move to a 100% clean grid (within reason - as no energy is ever fully clean with the production of resources etc.) - has been our energy security.

An image of a futuristic city with the title of the blog post.

Join me next time for:

  • The Smart Grid
  • and Energy Storage Systems
p.s. if anyone is interested in my previous work on this, all of my archived blog posts from January 2024 should do the trick (apart from the last two which are on Cypress) - bearing in mind that the titles are just named after songs and might not be clear. These posts will probably be better as I have more experience now. Thanks! And the knowledge has really had time to mature.



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