The novel power system and dual carbon goals have driven the development of intelligent scheduling methods for active distribution network. Aiming at the economic and low-carbon shortcomings of existing intelligent scheduling methods for active distribution network, a proactive intelligent scheduling method for distribution network based on day-ahead and intra-day scheduling has been proposed. The current distribution network scheduling model adopts a double-layer structure, with the upper layer being constructed based on the comprehensive optimization of costs such as main network electricity purchase, network loss, energy storage, operation and maintenance, carbon emissions, and peak valley penalties. The lower layer adopts a comprehensive optimal construction of peak valley fines, carbon emissions, and electric vehicle charging costs. The optimal scheduling model of intra-day distribution network is constructed by means of day-ahead upper level model objectives and interruptible load compensation costs. The model is solved through an improved non-dominated sorting genetic algorithm-III（NSGA-III）. The superiority of the proposed method is verified through numerical examples. The results indicate that, the proposed method takes into account both economic and low-carbon aspects. Through joint day-ahead and intra-day scheduling, the problem of photovoltaic output fluctuations has been effectively solved, and the operational performance of the distribution network has been optimized. The total solution time is 412.11 seconds, the total cost is CNY 50 665.60, and the carbon emission cost is CNY 1 583.50. It can provide certain assistance for achieving the dual carbon goal.