Modelling spatial and temporal agent travel patterns for optimal charging of electric vehicles in low carbon networks

• Published in: 2012 IEEE Power and Energy Society General Meeting pp. 1 - 8
• Main Authors: Acha, S., van Dam, K. H., Shah, N.
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.07.2012
• Subjects: Agent based transport modelling; Batteries; Cities and towns; coordination of distributed energy resources; distribution network operation; electric vehicle charging; Electricity; Load flow; Load modeling; local smart-grids; optimal power flow; Vehicles
• DOI: 10.1109/PESGM.2012.6345579
• ISBN: 1467327271; 9781467327275
• ISSN: 1932-5517

The ability to determine optimal charging profiles of electric vehicles (EVs) is paramount in developing an efficient and reliable smart-grid. However, so far the level of analysis proposed to address this issue lacks combined spatial and temporal elements, thus making mobility a key challenge to address for a proper representation of this problem. This paper details the principles applied to represent optimal charging of EVs by employing an agent-based model that simulates the travelling patterns of vehicles on a road network. The output data is used as a reliable forecast so an optimal power flow model can devise optimal charging scenarios of EVs in a local electrical network. The effectiveness of the model is illustrated by presenting a multi-day case study in an urban area. Results show a high level of detail and variability in EV charging when a present-day carbon fuel mix is compared to one with lower carbon intensity.