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|Title:||Modelling spatial and temporal agent travel patterns for optimal charging of electric vehicles in low carbon networks|
|Keywords:||Science & Technology;Technology;Engineering, Electrical & Electronic;Engineering;Agent based transport modelling;coordination of distributed energy resources;distribution network operation;electric vehicle charging;local smart-grids;optimal power flow|
|place:||Engineering & Physical Science Research Council (EPSRC)|
|Description:||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.|
|Type Of Material:||Other|
|Appears in Collections:||Faculty of Engineering|
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