PREDICTIVE AI
WATCH
NOW with when there is a renewable energy supply , then the CO₂ output can also be reduced .
“ The changing dynamics of battery and EV storage , as well as the activities of prosumers , are making the electricity grid increasingly unpredictable ,” Wilson adds . “ In a paradigm like this where statistical models are unable to deal with the number of unknowns , we can use machine learning models and start to trail more novel , or ‘ alternative ’, data sources .”
In his role , Wilson oversees how data generated by other sectors can be shared with the energy supply industry , for example , a telco client experiencing unexpected extremes in power demand .
“ AI and energy efficiency is a topic all by itself and there are many mature solutions ,” he starts , giving another example . “ We partner with a firm that uses AI to predict when file servers will be in demand
and turn down the clock speed at other times , saving 15-30 % of energy needs .”
“ I took part in an energy industry round table where the strong consensus was that AI is more than a measure to improve efficiency . It was clear that executives viewed AI-driven optimisation as an essential stopgap while physical infrastructure catches up – taking us towards a more flexible , higher capacity , and lower-carbon future .”
Could predictive AI mitigate risks to the energy sector ? A big part of working to said lower-carbon future can be attributed to efficiency in other areas such as supply chain . This , along with other unpredictable problems like extreme weather events and cybersecurity threats , has a circular impact on the slickness of the sector ’ s operations and its green credentials as a result .
But both Wilson and Gault firmly believe that technology , such as predictive AI ,
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