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Smart grid design depends on the availability of realistic data. In the near future, energy demand by electric vehicles will be a substantial component of the overall demand and peaks of required power could become critical in some regions. Transportation research has been using micro-simulation based activity-based models for traffic forecasting. The resulting trip length distribution allows to estimate to what extent internal combustion engine vehicles can be substituted by electric vehicles. Second, combining the results emerging from activity based models with assumptions on electric vehicles market share, allows to predict energy and power demand in time and space. Furthermore, smart grid management effects can be investigated using activity based models because generated schedules determine how charging periods can float in time. This paper presents results calculated for the Flanders region.