Elastic Scheduling Strategy for Electric Vehicles Based on Online Ride-Hailing Mode

Electric vehicles (EVs) exhibit significant uncertainty in responding to grid dispatch due to the influence of EV users’ judgments and other subjective factors, which affect grid scheduling. These subjective factors are difficult to model using conventional methods. Therefore, this paper proposes a flexible EV scheduling strategy based on the ride-hailing dispatch model. This strategy adopts an "order-grabbing" mechanism, where the dispatch center broadcasts demand, and EVs respond based on their current status. By dynamically adjusting the dispatch price, the strategy incentivizes EV participation, enhancing flexibility in EV-grid interactions. First, the initial dispatch price is set according to grid demand and EV battery capacity, and dispatch information is sent to EV users. A credit compensation mechanism is introduced to link EVs’ historical response with their rewards, thereby standardizing response behavior. Subsequently, a response willingness model is developed to associate the dispatch price and other influencing factors with response capacity, providing a basis for price adjustments. MATLAB simulations demonstrate that, the proposed method successfully completed scheduling in four different scenarios after 1-3 rounds of dynamic price adjustments, demonstrating the feasibility of the strategy. The final average response error using the proposed method was 25 kWh, representing a 61.53% reduction compared to the benchmark method, while scheduling costs decreased by 10.81%, validating both the accuracy and economic efficiency of the strategy. Compared to existing studies, this paper innovatively applies the ride-hailing model’s concepts of broadcast demand and order-grabbing response to effectively address the subjective uncertainty of EV users in the response process.