Real-Time Distributed Optimisation of Dualed Transport & Electrical Networks
Lead Participant:
CITY SCIENCE CORPORATION LIMITED
Abstract
The introduction of electric vehicles presents extensive new challenges for infrastructure planning and operation, in particular if the grid electricity is to be powered by renewables. For example, to enable optimised, automated control of charge/discharge profiles in grid-based or private wire battery storage systems, such systems will require extensive information and predictive data drawn from the transport network. Similarly, to optimise routing of electric/zero emission vehicles, routing systems will require extensive information and predictive data drawn from the electrical or hydrogen fueling network. In some cases, both networks may need to be optimised simultaneously.
Our vision is therefore to provide a fully integrated, real-time transport-electric-hydrogen network simulation and optimisation engine to enable complex optimisations to be run across these multiple networks to deliver the most cost-effective planning and operation of new transport-integrated electrical/hydrogen systems.
Our vision is therefore to provide a fully integrated, real-time transport-electric-hydrogen network simulation and optimisation engine to enable complex optimisations to be run across these multiple networks to deliver the most cost-effective planning and operation of new transport-integrated electrical/hydrogen systems.
Lead Participant | Project Cost | Grant Offer |
---|---|---|
CITY SCIENCE CORPORATION LIMITED | £187,028 | £ 130,920 |
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Participant |
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UNIVERSITY OF EXETER | £79,906 | £ 79,906 |
People |
ORCID iD |
Jo Muncaster (Project Manager) |