Browse Publications Technical Papers 2015-01-0304

Quantifying the Flexibility for Electric Vehicles to Offer Demand Response to Reduce Grid Impacts without Compromising Individual Driver Mobility Needs 2015-01-0304

Electric vehicles (EVs) enable improved vehicle efficiency and zero emissions in population centers, however the large loads from EV charging can stress grid systems during periods of peak demand. We apply detailed physics-based models of EVs with data on how drivers use their cars to quantify the ability for EVs to reduce their charging during periods of peak demand, i.e. as in a demand response program. A managed charging controller is developed and applied within the vehicle-to-grid simulator (V2G-Sim) which charges vehicles during demand response (DR) events only if charging is required to satisfy anticipated mobility needs for a given driver over the next 24 hours.
We find that up to 95% of EV charging loads can be removed during DR events without compromising the mobility needs of individual drivers. This value is found by comparing the charging loads of EVs using the managed charging controller against an uncontrolled charging case. Simulations are conducted with parametric sweeps of several important variables to understand the sensitivity of EV load reduction potential to these variables. For instance, demand response events are simulated at different times of day, and for different durations. It is shown that the EV charging load reduction potential is lower if DR events occur at later times of day; however the percentage reduction in EV charging load during these DR events is always above 75%. Further, we quantify the impact of uncertainty in the anticipated travel itineraries of individual drivers and it is shown that the DR load reduction potential from EVs decreases as greater levels of uncertainty must be accommodated. However, it is shown that even if managed charging for DR must accommodate substantial levels of uncertainty in individual travel itineraries, the DR load reduction potential is greater than 65%. Finally, we show that significant grid demand peaks are created if EV charging of many vehicles simultaneously resumes at the end of a DR event. We show that the post-DR peak from EV charging can be substantially reduced and pushed to later hours of the day if EV charging gradually resumes over a time window after the end of the DR event.
These findings show that EV loads are highly flexible, even while accommodating for highly uncertain individual travel needs, and that additional stress on the grid from EV charging is almost entirely eliminated during DR periods when EV charging is properly coordinated.


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