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The vehicle-to-grid (V2G) concept utilises electric vehicles as distributedenergy storage and thus may help to balance out the intermittent availabilityof renewable energy sources such as photovoltaics. V2G is therefore consideredto play an important role for achieving low-carbon energy and transportationsystems in cities. However, the adequate planning of city-wide V2Ginfrastructures requires detailed knowledge of the aggregate mobility patternsof individuals and also needs to keep track with ongoing developments of urbantransportation modes. Here, we introduce an initial framework that inferspopulation-wide mobility patterns from anonymised mobile phone location dataand subsequently superimposes a vehicle charging and discharging scheme. Theframework allows for the estimation of the aggregate V2G energy supply anddemand at fine-grained spatial and temporal scales under a given electricvehicle usage scenario. This information provides an adequate basis forassessing the role of V2G in the context of maximising the deployment ofphotovoltaics, as well as for the sizing and placement of the required vehicle(dis)charging infrastructure. The proposed framework is applied to Singapore asa case study.

Using Mobility Patterns for the Planning of Vehicle-to-Grid Infrastructures that Support Photovoltaics in Cities