How AI is ‘bending the curve’ on energy transition innovation
Collaboration and speeding up development are key for advancing AI in the energy sector, panellists in a session at Enlit Europe in Milan agreed.
The panel, moderated by Stavros Stamatoukos, Policy Officer for Digitalisation and AI in the EU’s DG Energy, addressed three questions: How is AI being used in the energy sector? What is coming next? and, How to make it happen faster?
With these it is intended to provide input to a planned EU roadmap and strategy for AI in the energy sector, which has been tasked to the incoming commissioner.
Opening the discussion for the grid operators, Nicoletta Rocca, Enel Global Services’ Head of Data Governance and Intelligence Delivery, said that AI was already widely used in the sector, with examples she cited including predicting renewables output and in the case of generative AI a mobile ‘assistant’ for field operators.
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“AI is also the swiss knife of our predictive maintenance,” she commented, adding another use case.
Joao Nascimento, Global Head of Digital at EDP, said his company’s approach is similar to that of Enel and highlighted the aim to extract the maximum value from the existing asset fleet.
Pointing to the need for a good digitalisation strategy and the fact that it necessitates a cultural change, Marco Barra, chief executive of Bludigit, added: “It’s clear that AI is revolutionising the energy sector.”
Turning to the services side, Andrew Scobie, chief technology officer of Enoda, commented on the use of AI to manage data rapidly.
The point also was made by Per Christian Honningsvaag, EMEA Business Leader, Energy & Resources at Microsoft, speaking for the vendor side of AI, who said AI and large and small language models are “bending the curve on innovation”.
As an example he cited material science with a project with PNNL involving processing 32 million new material candidates for batteries down to a shortlist of 18 potentials.
“That is taking lifetimes of [human] processing into days.”
Devrim Celal, Chief Marketing and Flexibility Officer at Kraken, highlighted its use to engage consumers.
“We started using large language models for [AI/ML] training in January 2022 and customer service representatives have been able to [respond to customer communications] spot on.”
The way forward for AI
Having set the scene on some of the activities under way the discussion turned towards the future, with each of the panellists commenting on issues such as governance, financial support, guidelines for regulators on customer data use, cybersecurity and the growing energy consumption of AI and its inclusion in planning.
“We need incentives to do more rather brakes to do less,” commented Nascimento on potential regulation, while Barra called for a unified industry approach.
Rocca highlighted people and collaboration as key and Scobie posited being able to innovate our way forward.
Celal suggested that guidelines rather then regulation should be provided by regulators, while Honningsvaag called for a “responsible AI” approach.
Summing up, Stamatoukos said: “We want to be positive and optimistic that the benefits outweigh any negative effects.”
Originally published on enlit.world
