Optimizing electric grids and charging infrastructure for mass electric vehicles penetration
Big data analytics and artifificial Intelligence to support electric vehicle grid readyness
Canada has an ambitious program to lower GHG emissions in all economic sectors to help meet its environmental targets. As transportation is one of the main GHG contributors, electrification can help the sector move to lower emission alternatives. Mass transportation electrification, however, is a new research field where there is a lack of knowledge on the impact that large electric vehicle (EV) fleets will have on the transmission and distribution electricity grids, and on the required charging infrastructure.
CanmetENERGY in collaboration with academia and private industry partners is applying AI and BDA techniques to large field data sets to analyze techno-economic factors, environmental considerations and drivers’ social behavior to predict and forecast their cumulative impact on the charging infrastructure, future grid extensions and utilities generation capacities.
The project will provide tools and knowledge to utility planners, policy makers, university researchers and consultants including:
- Models and databases for making sound business and operational decisions;
- Insights on current and future electricity use;
- Insights on charging, discharging and driving behaviour patterns; and
- Valuable information to help electricity distribution companies to optimize their existing distribution grids to accept large EVs penetration.
- Natural Resources Canada’s existing charging station dataset, comprised of over 1,000,000 data records from large fleets of electric vehicle.
Collaborators and Partners
- NRCan CanmetENERGY-Ottawa Research Centre
- NRCan Office of Energy Efficiency
- NRCan Office of Energy Research and Development
- Transport Canada
- Environment and Climate Change Canada
- University of Waterloo
- University of Oshawa Institute of Technology
- Date modified: