## 6 Example Analysis
Compared with Scenario 1, the costs of the subsystems are lower under Scenario 2; compared with Scenario 2, the costs of Subsystem 1 and Subsystem 2 are lower under Scenario 3, but the cost of Subsystem 3 is higher. The reason is that the subsystems are in a cooperative mode under Scenario 3 and Scenario 4. In this case, the objective function is to minimize the total operating cost of the system, resulting in the increase in the costs of some subsystems. For this reason, the method of asymmetric Nash bargaining is used in this paper to reallocate and adjust the cost of each subsystem. Tables 3 and 4 show the process of each subsystem bargaining under Scenario 3 and Scenario 4, respectively. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Scenario** & **Cost of System** & **Cost of Carbon** & **Total Cost/Yuan** \\  & **Operation/Yuan** & **Emission/Yuan** & **Total Cost/Yuan** \\ \hline Scenario 1 & 24,662.07 & 46,820.99 & 71,483.01 \\ Scenario 2 & 22,837.84 & 0 & 22,837.84 \\ Scenario 3 & 22,422.13 & 0 & 22,422.13 \\ Scenario 4 & 23,438.66 & 0 & 23,438.66 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Total cost of the system, the cost of system operation, and the cost of carbon emission under four scenarios. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Scenario** & **IES 1/Yuan** & **IES 2/Yuan** & **IES 3/Yuan** \\ \hline Scenario 1 & 27,497.96 & 21,226.30 & 22,758.74 \\ Scenario 2 & 9993.15 & 6276.47 & 6568.21 \\ Scenario 3 & 7576.17 & 7779.87 & 7066.09 \\ Scenario 4 & 7938.73 & 8096.70 & 7403.22 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Costs of three gas–electric IES. It can be seen from Tables 3 and 4 that after the process of bargaining transfer, the cost of each subsystem has been reduced compared with the cost under independent operation, so that the stability of the alliance and cooperation of gas-electric IESs is enhanced. In addition, the contribution of each subsystem is specifically considered in the process of redistributing the cost of each subsystem. For Scenario 3, the cooperation surplus of Subsystem 1, Subsystem 2, and Subsystem 3 are CNY 91.6, CNY 207.69, and CNY 116.4, respectively. This shows that Subsystem 2 contributes the most in the process of energy sharing, followed by Subsystem 3 and Subsystem 1. For Scenario 4, the cooperation surpluses of Subsystem 1, Subsystem 2, and Subsystem 3 are CNY 812.8, CNY 21.34, and CNY 1665.04, respectively. This shows that Subsystem 3 contributes the most in the process of energy sharing, followed by Subsystem 1 and Subsystem 2. In summary, the adopted method of asymmetric Nash bargaining makes each gas-electric IES more profitable than that under independent operation. Meanwhile, the contribution of each IES to energy sharing is evaluated in the distribution process, so that the scheme proposed is more scientific and reasonable. The iterative convergence of the robust optimization model under Scenario 4 is shown in Figure 6:  
It can be seen from Figure 6 that after eight iterations of the upper intelligent algorithm, the total operating cost of the three systems converges to CNY 23,438.66. In other words, the extreme scenario set that leads to the worst economic performance of the three systems is found through iteration, which further illustrates the effectiveness of the algorithm. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Mode** & **Subsystem 1/Yuan** & **Subsystem 2/Yuan** & **Subsystem 3/Yuan** \\ \hline Prebargaining & 7938.73 & 8096.70 & 7403.22 \\ Bargaining transfer & +1541.62 & \(-641.57\) & \(-900.05\) \\ Postbargaining & 9480.35 & 7455.13 & 6503.17 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Process of each subsystem bargaining under Scenario 4. Figure 6: Iterative convergence of the robust optimization model under Scenario 4.