Using activity-based modeling to predict spatial and temporal electrical vehicle power demand in Flanders

Abstract

Electric power demand for household generated traffic is estimated as a function of time and space for the region of Flanders. An activity-based model is used to predict traffic demand. Electric vehicle (EV) type and charger characteristics are determined on the basis of car ownership and by assuming that EV categories market shares will be similar to the current ones for internal combustion engine vehicles (ICEV) published in government statistics. Charging opportunities at home and work locations are derived from the predicted schedules and by estimating the possibility to charge at work. Simulations are run for several EV market penetration levels and for specific BEV/PHEV (battery-only/pluggable hybrid) ratios. A single car is used to drive all trips in a daily schedule. Most of the Flemish schedules can be driven entirely by a BEV even after reducing published range values to account for range anxiety and for the over-estimated ranges resulting from tests according to standards. The current low tariff electricity period overnight is found to be sufficiently long to allow for individual cost optimizing while peak shaving overall power demand.