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This paper studies the relationship and differences between carbon emissions and industrial development in four countries with different development levels from a global perspective. First, the Tapio decoupling model was established, and the overall dependence of countries of various development levels on carbon emissions was analyzed from strong to weak. Then, establish a panel data model to study the influencing factors of carbon emissions in countries with different development levels from 2015 to 2019. The results show that the added value of industry and agriculture has a significant positive effect on carbon emissions in countries of various development levels, and forest area has a significant negative effect on carbon emissions. Developed countries are still the largest emitters. Therefore, industrial and agricultural production is still the most important factor affecting carbon emissions, and the increase in forest area helps reduce the impact of carbon dioxide.

In the intelligent distribution network environment, the demand side resources (DSR) are the electric vehicle, energy storage, controllable load and other resources located in different locations, showing the characteristics of small single capacity and decentralized layout. How to build a multi time scale integrated scheduling framework of demand side resources and renewable energy, to schedule the distributed demand side resources in an orderly manner, and to realize the efficient integration of demand side resources and renewable energy, are the key problems of demand side resources participating in grid scheduling. Based on this, this paper proposes a multi time scale integrated scheduling method based on hierarchical scheduling for DSR and renewable energy in intelligent distribution network, and uses the modified cuckoo search algorithm (MCS) to solve the problem. The effectiveness of the proposed model and algorithm is verified by the integrated scheduling of electric vehicles and renewable energy in intelligent distribution network.