## 6 Example Analysis  
The first thing The scenarios considered in this paper cover three kinds of gas-electric IES. The specific parameters are: the upper and lower limits of P2G output are 800 kW and 0, respectively, with the efficiency being 60%; the upper and lower limits of carbon capture output are 100 kW and 0, respectively, with the carbon dioxide capture rate being 90% and the emission intensity being 0.2; the electric and gas loads can be adjusted within a certain range, with the total amount of electric and gas loads before and after adjustment remaining unchanged, and the maximum allowable adjustment proportion of electric and gas loads in each period within a day being 5% and 3%, respectively; the rated capacity and upper limit of charging and discharging power of the energy storage battery are 300 kWh and 60 kW, respectively, with the maximum and minimum values of the state of charge being 0.9 and 0.1, respectively, with the initial value of the state of charge being 0.2, and the charging and discharging efficiency coefficients both being 0.95; and the rated capacity and upper limit of gas storing and discharging power of the gas tank are 60 kWh and 12 kW, respectively, with the maximum and minimum values of the state of charge being 0.9 and 0.1, respectively, with the initial value of the state of charge being 0.5, and the charging and discharging efficiency coefficients both being 0.95. The predicted values of renewable energy output and load in the three subsystems are shown in Figures 3-5. Under the compiling environment of MATLAB 2021a, the Yalmip language was used in this paper to call CPLEX for a solution. Figure 3: Predicted values of renewable energy output and load in system 1. Figure 4: Predicted values of renewable energy output and load in system 2. Figure 5: Predicted values of renewable energy output and load in system 3. To verify the effectiveness of the model proposed in this paper, the following four scenarios were set:  
Scenario 1: each integrated energy park operates independently, without a carbon capture device and electric-to-gas converter. Scenario 2: each integrated energy park operates independently, with a carbon capture device and electric-to-gas converter. Scenario 3: all integrated energy parks operate cooperatively, with a carbon capture device and electric-to-gas converter. Scenario 4: the robust optimization model of multiple regional IESs is considered based on Scenario 3. Table 1 shows the total cost of the system, the cost of system operation, and the cost of carbon emission under the four scenarios, and Table 2 shows the costs of the three gas-electric IESs. It can be seen from Table 1 that the total cost of the system, the cost of system operation, and the cost of carbon emission show a decreasing trend from Scenario 1 to Scenario 3, while these costs increase under Scenario 4 compared with Scenario 3. The reason is that under Scenario 1, the lack of energy conversion devices such as an electric-to-gas converter and a carbon capture device in each gas-electric IES leads to the poor energy conversion and carbon dioxide absorption capacity of the system and the highest costs under this scenario; the incorporation of an electric-to-gas converter and carbon capture device under Scenario 2 improves the energy utilization rate in each system and, thereby, reduces the cost of each system; under scenario 3, all subsystems can share electric and gas energy, and the energy coupling utilization among subsystems further enhances the overall energy utilization rate of the system. Because the uncertainties of the system in renewable energy and load are considered under Scenario 4, each cost under the worst scenario is higher than that under Scenario 3, showing the impact of extreme natural scenarios on the dispatching cost of the system. Table 2 shows that the systems are independent of each other under Scenario 1 and Scenario 2.