With the intensification of energy shortages and climate warming, how to achieve the coordinated dispatch of electric vehicles (EVs) and high-proportion renewable energy systems (RESs) in the power system has been attracting more and more attentions. From the generation side and the distribution side, this work investigates the problem of large-scale EVs charging and discharging scheduling via the collaborative optimization among thermal power plants, wind and solar power, and EVs. To this end, an energy scheduling system (ESS) including power transmission and distribution is established, based on which a bi-level scheduling strategy is proposed. The upper level coordinately optimizes EVs, thermal power units, wind and solar power generation, and grid base loads to achieve the minimization of power supply costs. By introducing the node loss sensitivity (NLS) and node electricity price (NEP), the lower level allocates EVs to charging nodes to attain the minimization of the grid loss cost and charging cost. Finally, via the IEEE33-node standard power grid and the ESS model, it is verified that the proposed bi-level scheduling strategy can reduce the overall cost (node loss and charging cost) by 28.5%, and the wind curtailment rate and photovoltaic curtailment rate are 0.0% and 0.4%, respectively, making full use of renewable energy and adapting to its uncertainty.