Carbon-Aware Quantification of Real-Time Aggregate Power Flexibility of Electric Vehicles

Abstract

Electric vehicles (EVs) can be aggregated to offer flexibility to power systems. However, the rapid growth in EV adoption leads to increased grid-level carbon emissions due to higher EV charging demand, challenging grid decarbonization efforts. Quantifying and managing the EV flexibility while controlling carbon emissions is crucial. This paper introduces a methodology for carbon-aware quantification of real-time aggregate EV power flexibility based on the Lyapunov optimization technique. We construct a novel queue system including EV charging queues, delay-aware virtual queues, and carbon-aware virtual queues. Based on the evolution of these queues, we define the Lyapunov drift and minimize the drift-plus-penalty term to get the real-time EV flexibility interval, which is reported to the system operator for flexibility provision. To enhance EV flexibility, we integrate dispatch signals from the system operator into the queue updates through a two-stage disaggregation process. The proposed approach is prediction-free and adaptable to various uncertainties, including EV arrivals and grid carbon intensity. Additionally, the maximum charging delay of EV charging tasks is theoretically bounded by a constant, and carbon emissions are effectively controlled. The numerical results demonstrate the effectiveness of the proposed online method and highlight its advantages over several benchmarks through comparisons.