Charging Fast and Slow: Quantifying the Real-Life Value of EV Charging for Users, OEMs, and the Grid
Wednesday, Sep 23, 2026, 3:00 pm - 4:15 pm
Pierce Hall Room, 100F, 29 Oxford Street, Cambridge
A Harvard-China Project Research Seminar with Christian Kaps, Assistant Professor of Business Administration, Harvard Business School
Abstract: Managing electricity demand is critical for lowering the cost of electrified products, integrating intermittent renewables, and reducing grid expansion needs. With its often flexible demand, electric vehicle (EV) charging has long been considered a promising candidate, yet many managed charging programs have not scaled. We analyze why this is the case and identify several challenges to existing programs, focusing on two business models: smart electricity consumption (V1G) and demand response (DR). After grounding the analysis in a stylized model, we leverage a longitudinal dataset of over 20,000 EVs and 1.5 million charging events across the U.S. to empirically study managed charging. We find that V1G with time-of-use pricing saves EV owners up to $300 annually but increases the utility's wholesale generation cost, a misalignment that in 75% of markets cannot be costs-effectively eliminated by paying owners to adjust charge timing. For DR, the top 10% of customers provide 5.2 times the average vehicle's value, and only 9.4% of vehicles can be profitably enrolled. We identify which charging behaviors predict profitable DR customers and how this interacts with utilities' prices. We further analytically show when V1G and DR may be misaligned, and show empirically that V1G participation cannibalizes 16-46% of DR returns, highlighting challenges with stacking value streams. Our findings help EV manufacturers decide which programs to offer, in which markets, and which customers to target or behaviors to incentivize. We highlight where utilities and regulators should adjust tariffs to better align EV owners' incentives with market outcomes.
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Abstract: Managing electricity demand is critical for lowering the cost of electrified products, integrating intermittent renewables, and reducing grid expansion needs. With its often flexible demand, electric vehicle (EV) charging has long been considered a promising candidate, yet many managed charging programs have not scaled. We analyze why this is the case and identify several challenges to existing programs, focusing on two business models: smart electricity consumption (V1G) and demand response (DR). After grounding the analysis in a stylized model, we leverage a longitudinal dataset of over 20,000 EVs and 1.5 million charging events across the U.S. to empirically study managed charging. We find that V1G with time-of-use pricing saves EV owners up to $300 annually but increases the utility's wholesale generation cost, a misalignment that in 75% of markets cannot be costs-effectively eliminated by paying owners to adjust charge timing. For DR, the top 10% of customers provide 5.2 times the average vehicle's value, and only 9.4% of vehicles can be profitably enrolled. We identify which charging behaviors predict profitable DR customers and how this interacts with utilities' prices. We further analytically show when V1G and DR may be misaligned, and show empirically that V1G participation cannibalizes 16-46% of DR returns, highlighting challenges with stacking value streams. Our findings help EV manufacturers decide which programs to offer, in which markets, and which customers to target or behaviors to incentivize. We highlight where utilities and regulators should adjust tariffs to better align EV owners' incentives with market outcomes.
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