Optimal Pricing and Energy Sharing of EV Charging Stations With an Augmented User Equilibrium Model

With the proliferation of electrical vehicles (EVs), tariff-based monetary incentives (e.g., charging service fees, electricity prices) have been widey adopted by network operators to efficiently manage EV charging demands. The imposed tariff would enforce drivers to bear an extra travel expense for satisfying the charging demand distributions favored by network operators. Accurately modeling users' responsive behavior to price signals is a prerequisite for properly designing the tariff and achieving the desired goal. The present work bridges the gap of existing studies by proposing an augmented user equilibrium (AUE) model that captures EV users' equity-aware decision makings and closed-loop commuting behavior. The model enables network operators to consider 1) the acceptability of EV travelers on regulation policies and 2) the elasticity of EV charging demand as well its rebound effect. Based on the AUE model, we further investigate the optimal pricing and energy sharing strategy of the charging network operator, who aims to maximize his/her profit by tapping the flexibility of EVs and scheduling energy transactions among charging stations while respecting the operating constraints of power and transportation networks. Finally, a relaxation based iterative algorithm is devised to efficiently solve the mathematical problem with complementarity conditions. Numerical results on two test systems validate the effectiveness and merits of the proposed models and methods.