<![CDATA[With the growing global energy crisis and environmental problems, the large-scale deployment of electric vehicles (EVs) and various types of distributed renewable energy sources has become an important measure to promote sustainable development in China's power sector. However, the rapid increase in the penetration rate of these distributed resources has gradually increased the operational pressure on distribution networks. To effectively address this issue, this paper proposes a two-layer partitioned optimization scheduling strategy for the distribution network layer and the aggregation layer, considering the price-based demand response of EV users. The upper distribution network layer focuses on its own low-carbon and economic operation, establishing a low-carbon economic optimization scheduling model for the distribution network layer to allocate global resources and formulate energy interaction strategies and constraints between aggregation areas based on this. The lower layer first constructs a comprehensive partitioning scheme considering the electrical distance between nodes, the dispatchable potential of EVs, and the power balance of distributed resources. Then, aiming at the economic operation of the aggregation area itself, it establishes a price-based demand response model for EV users to achieve optimal scheduling of distributed resources in the aggregation layer. This study aims to achieve the economic and low-carbon operation of distribution networks through reasonable scheduling strategies, while meeting the charging needs of EVs and improving the utilization efficiency of distributed resources. Simulation results show that the proposed two-layer scheduling strategy can effectively mobilize distributed resources in the distribution network to meet the needs of system economic operation. After optimization at the distribution network layer, the daily operating cost is reduced from 11,551.88 yuan to 6,220.84 yuan, significantly improving economic benefits. Electric vehicles have achieved a reduction of 21.1% in load peak shaving. In conclusion, the two-layer partitioned optimization scheduling strategy proposed in this paper can effectively utilize distributed resources in distribution networks, reduce operation costs, and achieve economic and low-carbon operation of distribution networks.]]>
