Aiming at the problem that the uncertainty of wind and solar new energy output leads to the decrease of system emission reduction effect

a low-carbon adaptive optimization strategy of new energy system under carbon-green certificate joint trading mechanism is proposed. Firstly

the probabilistic power flow is used to calculate the random uncertainty of new energy output. Combined with the carbon emission flow theory of power system

the allocation result of carbon emission responsibility to the load-side subject is clarified by solving the node carbon potential and tracking the carbon flow. Secondly

a carbon-green certificate trading mechanism with carbon flow density and carbon emissions as comprehensive carbon indicators is constructed. The information entropy theory and conditional value-at-risk theory

which do not need to assume parametric distribution of carbon index data

are introduced for collaborative modeling. The quantitative results of the uncertainty risk level of new energy output are given. According to the quantified risk level

an adaptive ladder carbon price partition for different risk dynamic contraction and relaxation is established

which standardizes the carbon emission responsibilities of different users and realizes the deep coordination of carbon trading and green certificate trading in pricing rules and responsibility accounting. Finally

different schemes are compared and analyzed in the IEEE 14 node system. The results show that the proposed method can be adopted to effectively measure the impact of new energy uncertainty risk and realize the low-carbon economic operation of the system.