Incentive V2G pricing considering the opportunity cost irrational perception distortion of ride-hailing vehicles

• Behavioral vehicle-to-grid pricing captures drivers’ distorted opportunity costs. • Perceived incentive threshold shows a rise–decrease–rise pattern across modes. • Three revenue-based regimes explain heterogeneous ride-hailing participation. • Bounded rationality shifts usable flexibility versus linear expected-utility pricing. • Aggregator demand level determines required incentives and deliverable capacity. Conventional vehicle-to-grid (V2G) pricing often fails to incentivize participation by assuming full rationality, ignoring the opportunity costs and irrational perception distortions of ride-hailing vehicles (RHVs). To address this, driving-related revenue is quantified as passenger-carrying revenue (PCR) and integrated into a Prospect Theory-based framework. This approach models the nonlinear valuation of gains and losses using reference dependence to capture decision-making trade-offs between driving and discharging. Simulation results identify three behavioral paradigms: PCR-Deficient, PCR-Suitability, and PCR-Saturation. Unlike linear Expected Utility models, this framework reveals that optimal perceived incentives generally range from 1.22 to 3.82 CNY/kWh, governed primarily by target discharge volume rather than user class. Furthermore, sensitivity analysis regarding aggregator power demand indicates that under stable, low-demand conditions, price differentials between 0.6 and 2.0 CNY/kWh are sufficient to trigger participation. Conversely, high-demand emergency scenarios require incentives of 2.0 to 4.0 CNY/kWh to ensure grid stability. These findings bridge the gap between theoretical pricing and realistic behavior, offering actionable guidance for designing user-centered V2G tariffs that balance aggregator costs with driver participation.