Research on the Optimal Bidding Strategy of Electric Vehicle Aggregators in Power Markets Considering Uncertainties

With the rapid growth of electric vehicle (EV) numbers and their deep integration with smart grids, the role of Electric Vehicle Aggregators (EVA) in power markets is becoming increasingly important. This paper proposes a stochastic-robust joint optimization bidding decision model considering uncertainties. The model generates representative random electricity price scenarios using the K-means clustering method, applies robust control coefficients to handle the randomness of EV charging and discharging behaviors, and uses willingness-to-respond coefficients to simulate the uncertainties of EV responses. By solving the model, the proposed approach is validated, demonstrating good effectiveness and robustness under various scenarios and significantly enhancing the EVA ability to maximize profits in the power market.