Enhanced-Interval Optimal Scheduling of Power-Transportation Interconnected System Considering Pile (Station) Equilibrium Price

As the distribution network is affected by the high proportion of renewable energy connected to the grid and the disorderly charging of electric vehicles, how to formulate the optimal scheduling strategy to ensure the safety and stability of the system has become an urgent problem to be solved. Aiming at the uncertainty of the user behavior of the traffic network, a charging pile (station) pricing strategy based on stochastic user equilibrium (SUE) is proposed. The equilibrium electricity price of charging pile (station) is formulated to guide the traffic flow and realize the collaborative optimization of the distribution network. Considering the traffic congestion caused by user behavior, a congestion charging policy is proposed to promote static hybrid SUE. Its feasibility is proved by Karush-Kuhn-Tucker (KKT) condition and variational inequality. In addition, through the introduction of joint pricing center, charging pile (station) electricity price, and congestion charging policy are proposed. Aiming at the uncertainty of system, an enhanced-interval optimal method is established. Finally, the simulation analysis of the power-transportation interconnected system verifies that the congestion charging policy can optimize the unit output, and the enhanced-interval optimal method can solve the uncertain influence, reduce the system cost, and ensure the satisfaction of traffic users.