Electric vehicles (EVs) can break our dependence on fossil fuels in transport and energy sectors. However, mass adoption of EVs introduces significant and disruptive electricity demand to meet the charging needs of these vehicles. Vehicle grid integration strategies, underpinned by data science, ensure that electric vehicle charging infrastructure is synergistic with the electricity grid, reliable, cost effective and sustainable.
Explaining the science
The project aims to:
- Apply and develop data science methods and tools to help in the transformation of electricity and transport infrastructure into sustainable and efficient infrastructure, while maintaining reliable operation
- Contribute to open communication protocols for vehicle grid integration
- Contribute to open source software for vehicle grid integration
- Apply and develop privacy preserving methods for energy demand data
- Conduct security analysis to grid-integrated EV charging infrastructure (assessing security of communication, hardware and software)
- Devise response plans to potential security threats and attacks
- Assess several new technology pathways to help policy makers make informed decisions
This work can be applied in the automotive and energy industries to help empower companies to make informed investment decisions and develop products which are future-proof and user-centric. The work can also provide evidence to support informed energy and transport policy decisions.
- Paper: Energy Informatics. Collaboration with DTU. “Mind the gap- open communication protocols for vehicle grid integration”
- Poster: “Towards a Data Centric Approach for the Design and Verification of Cryptographic Protocols”, CCS '19 Proceedings of the 2019 ACM SIGSAC Conference on Computer and Communications Security.
- Response to government consultation on smart charging in support of planned smart charging legislation in 2020.
- All Out Politics (Sky News). Dr Myriam Neaimeh talks about the Government’s measures to support the uptake of electric vehicles
Researchers and collaborators
Former researchers and collaborators
- Eric Chan, Research Associate, Newcastle University
- Ridoy Das, Research Associate, Newcastle University
- Anna Hadjitofi, Data Scientist, Research Engineering Group, Turing
- Mark Turner, Head of Research Software Engineering, Newcastle University