Under the "dual carbon" goals, the rapid development of new energy sources poses challenges to the secure and stable operation of the power grid due to the uncertainty in their output. Active distribution networks have the capability to control various combinations of distributed energy sources, providing an effective solution to the current challenges of integrating new energy sources into the grid. Simultaneously, demand response, as an effective means of controlling load-side resources, when combined with active distribution networks, can effectively mitigate the impact of uncertainties on both the supply and demand sides of the grid. A proactive distribution network day-ahead optimization scheduling model was constructed based on the "source-grid-load-storage" coordinated optimization. The objective was to maximize the revenue of the active distribution network, taking into account the participation of electric vehicles in demand response, grid security, energy storage battery configuration, as well as the costs and constraints of each component unit. Simulation results demonstrate that the constructed proactive distribution network optimization scheduling model is reasonable, capable of reducing active power grid losses, decreasing peak loads, narrowing load peak-valley differentials, and ultimately enhancing the revenue of the distribution network.