What is the minimum required (and desired) data standards and processes are required to enable AI/ML to effectively engage with Energy System (e.g. optimising millions of distributed assets with greater precision thus reducing the reliance on blunt capacity market instruments)?
Background
BEIS has committed to ending the UK’s contribution to global warming by achieving net zero greenhouse gas emissions by 2050. Our work towards becoming a leader in green technologies and clean energy will drive economic growth, all whilst accelerating global climate action through strong international leadership.
Next steps
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Source
This question was published as part of the set of ARIs in this document:
Topics
Related UKRI funded projects
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AI-Powered Digital Twin for the Power System
The UK is committed to achieving Net Zero emissions by 2050 (BEIS, 2019). Achieving this requires extensive reconfiguration of our energy system from 'top-down' to 'bottom-up', integrating new low-carbon technologies (e....
Funded by: ISCF
Why might this be relevant?
The project specifically addresses the question by developing an AI-powered digital twin for the power system to optimize energy assets.
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Supergen Network Plus in Artificial Intelligence for Renewable Energy (SuperAIRE)
SuperAIRE aims to establish a world-leading network connecting academia, industries, and policymakers across the spectrum of artificial intelligence (AI) for renewable energy (RE), particularly wind, solar, marine, and b...
Funded by: EPSRC
Why might this be relevant?
The project specifically focuses on AI for renewable energy systems, addressing data standards and processes to optimize energy systems.
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Manchester Metropolitan University and Oak Tree Power Limited KTP 22_23 R3
To develop novel Artificial Intelligence and Machined Learning capabilities for a Sustainable Energy Management System....
Funded by: Innovate UK
Why might this be relevant?
The project focuses on developing AI and machine learning capabilities for a sustainable energy management system, which partially aligns with the question's objective.