About

In order to optimise UK energy and transport to help achieve Net Zero aims, AI for Net Zero will develop faster and more accurate models of their physical systems. We will utilise state of the art modelling techniques, energy-efficient AI algorithms and the latest computing hardware. We aim to undertake engagement and dissemination activities across industries, the government and policymakers to maximise the impact of these findings.

We are funded by UKRI/ESPRC under the following grant codes: EP/Y004450/1, EP/Y004841/1, EP/Y004930/1, EP/Y005619/1

Research Themes

Policy projects

Translating our research into effective evidence which policymakers can use to work towards a net zero society.

We will do this by collaborating across the policy landscape, working with our team, the wider scientific community, members of the public, government and other organisations. We will ensure that multiple stakeholders are simultaneously involved in the communication of our research, allowing policies to make use of, and even drive, high-quality and impactful research.

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Net Zero projects

Applying our AI technologies and framework to three test cases - wind farms, hydrogen energy and vehicle aerodynamics - to demonstrate their potential to help achieve carbon net zero.

We will practically address key design questions for three energy and transport systems with real-time, scalable, and accurate models: (i) optimisation of wind farms to maximise power output; (ii) modelling and control of hydrogen-based systems to make them operate in safe conditions; and (iii) cooperation of road vehicles aerodynamics to minimise the aerodynamic drag.

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AI projects

Developing virtual replicas (digital twins) of physical systems to optimise power output and usage in the safest way.

The overarching goal is to create real-time Digital Twins that are (i) efficient, both in terms of performance and their use of resources; (ii) consistent with the physics of the problem, such as the laws of mechanics and thermodynamics; (iii) adaptive; (iv) real-time; and (iv) able to manipulate the engineering system to control it and make it operate in safe and optimal conditions.

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