## 6 Simulation and Analysis
### Cross-RIES Optimization Results and Analysis
#### 6.4.4 Sensitivity Analysis  
1. Carbon-trading prices and green-certificate-trading prices;  
Using a baseline value of 50 CNY per unit, the green-certificate-trading prices are set to vary in increments of \(\pm\)25 CNY. A price of 0 CNY per unit represents a scenario considering only the carbon-trading mechanism, i.e., the CET-CRIES scenario. Using a baseline value of 58 CNY per ton, the carbon-trading prices are set to vary in increments of \(\pm\)20 CNY. A price of 0 CNY per ton represents a scenario considering only the green-certificate-trading mechanism, i.e., the GC-CRIES scenario. The renewable energy quota is set at 10%. Figure 13 illustrates the impacts of variations in carbon-trading prices and green-certificate-trading prices on the system's carbon emissions. Figure 11: The load-bearing rate and carbon emissions of each RIES in the four carbon-emission reduction policy scenarios. From the analysis, it can be observed that when the carbon-trading price is 0 CNY per ton, i.e., in the GC-CRIES scenario, as the green-certificate-trading price increases from 25 CNY per unit to 125 CNY per unit, the system's carbon emissions decrease from 4105 tons to 3926 tons, resulting in a reduction of 4.36%. When the green-certificate-trading price is 0 CNY per unit, i.e., in the CET-CRIES scenario, as the carbon-trading price increases from 18 CNY per ton to 98 CNY per ton, the system's carbon emissions decrease from 3524 tons to 3312 tons, resulting in a reduced rate of 6.02%. When the system transitions from the Reference-CRIES scenario (with both the carbon-trading and green-certificate-trading prices at 0) to the GC+CET-CRIES scenario (with a green-certificate-trading price of 125 CNY per unit and a carbon-trading price of 98 CNY per ton), the system's emissions decrease from the maximum value of 4648 tons to the minimum value of 3081 tons, resulting in a reduction of 33.71%. It can be seen that the increase in prices for both mechanisms effectively suppresses the system's carbon emissions, which is consistent with existing research findings [47; 48; 49], with the impact of carbon-trading price variations being more pronounced. The reason behind this can be attributed to the fact that HP-RIES and CP-RIES have the production capacity of renewable energy, making the constraint of the green certificate quota requirements relatively weaker for these system configurations. Figure 12: Carbon emission intensities and marginal abatement costs in four carbon-emission reduction policy scenarios. Figure 13: Sensitivity analysis of the impacts of carbon-trading prices and green-certificate-trading prices on carbon emissions. This constraint primarily affects the FP-RIES system, which relies solely on traditional fossil energy. Table 12 illustrates the changes in the load allocation rates for FP-RIES when the renewable energy quota is set at 10%. It can be observed that an increase in green certificate prices leads the system to reduce its own load allocation in order to lower the cost for purchasing green certificates. On the other hand, variations in carbon-trading prices affect all the RIES systems. When carbon-trading prices increase, the entire system needs to actively promote low-carbon technologies and strive to reduce carbon emissions to avoid high carbon penalty costs. Green-certificate-trading prices and renewable energy quotas. In this section, this study takes 10% as the baseline value and explores the impact of variations in renewable energy quotas within a range of \(\pm\)2% on carbon emissions across RIES systems. The results are presented in Figure 14. With fixed green-certificate-trading prices of 25 CNY per unit, 50 CNY per unit, 75 CNY per unit, 100 CNY per unit, and 125 CNY per unit, as the renewable energy quota increases from 4% to 14%, the reduction rates of the system's carbon emissions are 2.34%, 6.92%, 6.62%, 7.07%, and 7.15%, respectively.