###### Abstract
P2G technology requires CO2 as the raw material in the process of synthesis of natural gas, which makes it possible to absorb wind and reduce carbon at the same time. Relevant studies have paid little attention to the carbon emission benefit of P2G [10; 11], and the incentive space brought by the benefit has not been further explored. After taking into account the wind curtailment and carbon emission benefits of P2G, P2G will have higher economic efficiency. As the interaction between the power system and the natural gas system increases, on the one hand, the power system needs to consider the reliable and safe supply constraints of the natural gas network when dispatching [12]. On the other hand, the optimized operation of IPGES is the basis for optimizing resource allocation and improving energy utilization efficiency, and is of great significance for improving the comprehensive benefits of the system [13; 14]. The power grid and natural gas network, as the carriers of energy transmission, are mainly considered as power flow operation constraints in the model [15; 16]. [PERSON] et al. [17] present a novel hybrid information gap decision theory stochastic co-optimization problem for integrating electricity and natural gas networks. Moreover, the power-to-gas technology and demand response program are considered in the proposed model for increasing the wind power dispatch. The power generation of renewable energy is random and difficult to predict. Therefore, the entire energy system also faces the challenge of accommodating a large amount of random renewable energy. Two main approaches adopted by many researchers for including uncertainty which are robust optimization and stochastic programing. In [18; 19] the stability of the power system is analyzed using robust optimization considering a high level of wind generation. Although robust optimization has been applied to circumvent the challenges of uncertainty of wind generators, the main disadvantage is that it only considers the worst case in the analysis of renewable energy sources (RES) penetration level. The robust optimization framework increases the operating cost that affects the optimal dispatch scheme. In contrast to robust optimization, the stochastic programming approach uses a large number of scenarios to handle uncertainty in RES generation [20; 21]. In the scenario generation method, a large number of scenarios are generated through the probability distribution of random variables. Developing the low carbon power sector is of great economic significance under carbon policies. Carbon trading mechanism is an important way to balance environmental protection and economic benefits, and can stimulate enterprises to reduce carbon emissions independently. It is mainly divided into traditional unified carbon trading and lad-der-type carbon trading [22; 23]. In [24; 25], low-carbon dispatching models of energy systems based on carbon trading mechanisms have been established respectively, which have guiding significance for the carbon trading cost analysis of integrated energy systems. In [26], a risk-constrained two-stage stochastic dispatch model based on the chance-constrained programming is proposed, in which the carbon capture systems, carbon trading, demand response and renewable generation are considered. [PERSON] et al. [27] analyzed carbon emission and total cost of the system without considering the carbon trading mechanism, considering traditional carbon trading mechanism and considering ladder-type carbon trading mechanism respectively, and proved the rationality of adopting the ladder-type carbon trading mechanism for the low-carbon economic dispatching of the integrated energy system. [PERSON] et al. [28] propose the concept of reward coefficient, introduce the reward and punishment ladder-type carbon trading into the planning model, and establish an energy center planning model with the goal of minimizing the sum of system investment cost, operation cost and carbon transaction cost.