Transitions to electric vehicles are expected to increase electricity use in residences, where most drivers tend to recharge. We develop a mathematical programming framework for shifting residential EV charging during low electricity pricing hours to minimize the additional electricity costs that a household incurs from charging its vehicle. The model also accounts for household and community preferences through four secondary objectives: charging as soon as possible on arrival, charging as late as possible before departure, charging for valley filling and peak shaving of residential load, and charging in a shared community hub by using a fast charging station.
We analyze granular residential energy data from a sample of Austin households in 2018 and compare electricity bills under four pricing schemes, including flat rates and time-of-use rates, both with and without a separate meter for EV charging. The findings show that all four secondary charging objectives avoid on-peak charging periods and reduce households’ overall daily electricity costs while surfacing trade-offs in flexibility, charger utilization, and grid load smoothing.
Recognition: 2nd Place, INFORMS Mini Poster Competition, 2021.