What’s it?
With the widespread adoption of electric vehicles (EVs), it is crucial to plan for charging in a way that considers both EV driver behavior and the electricity grid’s demand. Here, we integrate detailed mobility data with empirical charging preferences to estimate charging demand and demonstrate the power of personalized shifting recommendations to move individual EV drivers’ demand on the grid out of peak hours. We find an unbalanced geographical distribution of charging demand in the San Francisco Bay Area, with temporal peaks in both grid off-peak hours in the morning and on-peak hours in the evening. Aligning with mobility patterns, our strategy effectively shifts demand to off-peak times. With the 2050 target of 90% EVs, this shifting reduces total on-peak charging demand by 61%, which could require over ∼18,000 additional level 3 chargers. We recommend building more charging stations and implementing shifting recommendations for EV grid integration.
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For more information please refer to Full Paper.