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Challenge / Goal

The challenge was to predict the charging demand of the future including all mobility modes available in the city of Espoo. The available charging data is very scarce, and it is not representative of what can be expected 10 – 20 years from now. The charging demand could be predicted through vehicle simulations, but a detailed simulation of all vehicles operating in the city was not possible in practice due to a lack of sufficient data as well as the high computational load such a simulation would create.

Solution

Statistical data on the usage of vehicles was gathered from various sources. The output of an activity-based transportation model was used to get data on passenger cars, whereas public transportation schedules were used for buses and traffic counts for trucks. A set of probable mobility patterns for the vehicles were formed based on the data and the energy need of each vehicle was roughly estimated. The temporal pattern of the charging demand was then formed by using a graph-based optimization algorithm and aiming at recharging each vehicle at the most optimal time instant. Scenarios with different pricing curves and different charging power levels were evaluated using the developed methodology.

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Time period

Planning time: Less than 6 months

Implementation time: 6 months to 1 year

Implementers

VTT and Plugit

Service providers

VTT

End users

VTT

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