AI simulations model carbon tax to help inspire future net-zero shipping
Artificial Intelligence technologies from the University of Southampton are helping to deliver more efficient shipping by providing insights, derived from millions of simulations, on the most effective strategies to achieve net-zero targets.
The research collaboration with Shell Shipping and Maritime analyses carbon tax scenarios before predicting the impact of green strategies such as adjusting voyage routes, installing energy efficient technologies and applying carbon offset incentives. The model is intended to provide information and support as shipping companies aim for a net-zero emissions industry.
The expanding analysis is part of the University and Shell's partnership work in the Centre for Maritime Futures, which aims to transform the energy shipping industry to be safer, cleaner and more efficient through ground-breaking digital and technological advances.
Professor Ramchurn, Co-Director of the Centre for Maritime Futures, says: "Optimising the transition of shipping fleets to cleaner and more efficient technologies against a backdrop of uncertainty requires trialling a range of future scenarios. We are addressing this challenge through a range of AI and machine learning solutions embedded in a high fidelity simulation platform."
Dr Gerding, Director of Southampton's Centre for Machine Intelligence, adds: "Researchers have created a detailed carbon tax report, highlighting different carbon tax regimes at national, regional and international levels, currently enforced or planned. We developed an agent-based simulation to model different carbon tax regimes, shipping and commodity markets, and provide insights in order to help shipping companies better manage their emissions down."
The simulation system is being built in stages, with each stage adding new features to different apps allowing concurrent and independent development while also ensuring gradual enhancement in functionality, parallel deployment of resources based on their speciality.
To analyse the behaviours and better model the overall simulation system, a detailed data analysis was carried out on data provided by Shell for multiple vessels in their fleet.
The partners' next goal is to ensure that all user requirements are captured to further develop the platform to allow users to run 'what-if' scenarios. This will allow the creation of a multi-user testbed that will enable traders to make better trading decisions and shipping operators to predict the performance of future fleet profiles.
Professor Ramchurn says: "Our work will underpin the design of next generation Uber-freight models that will enable the dynamic routing of vessels and enable a smooth transition to net-zero shipping using green hydrogen both as a fuel and cargo."