## 4 Case Studies
### Comparative Analysis of the Proposed Incentive Mechanism and the Existing Mechanisms
#### 4.3.1 Scenario 1: Annual Wind Power Utilization of Approximately 2000 h  
Beginning in 2021, China no longer subsidizes newly approved onshore wind power projects. The emergence of renewable energy certificate trading has also played a role in promoting the development of wind power. However, the trading of renewable energy certificates is not active and widespread enough in China. The energy storage capacity subsidy incentive is relatively common in China. The proposed bus carbon incentive mechanism is based on the carbon perspective. The existing energy storage capacity subsidy incentive mechanism and renewable energy certificate trading mechanism are both energy-based incentive mechanisms. Based on these practical situations, this paper compares  
Figure 6: Bus carbon intensities at optional WT locations before planning.  
the proposed incentive mechanism with the two energy-based incentive mechanisms in practice. As a result, the following three cases were set up for comparison.  
* Case 1: The proposed bus carbon intensity incentive mechanism;
* Case 2: The energy storage capacity subsidy incentive mechanism;
* Case 3: The energy storage capacity subsidy incentive mechanism and renewable energy certificate trading.  
The incentives in the three cases were tested in the same system planning model. The planning results are shown in Table 7. Due to the poor wind resource, the wind turbine was not planned in Case 2 without wind-related incentives. Compared with the total carbon emissions of the original system, 39,150.4 ICO\({}_{2}\), the carbon reduction rates of Case 1, Case 2, and Case 3 are 11.32%, 1.06%, and 5.02%, respectively. As seen in Figure 8, compared with Case 2, the proposed mechanism of Case 1 can effectively promote wind power and energy storage configuration with a significant carbon reduction effect. Case 1 still has a better carbon reduction effect compared to Case 3 and has a similar total fixed investment cost. Thus, with the proposed incentive mechanism, the model can plan more reasonable wind turbine and energy storage capacities and effectively promote the system to reduce carbon emissions.  
Figure 9 visualizes the carbon intensity variation of Case 2 and Case 3 for all buses throughout the day. The bus carbon intensity diagram of Case 1 and the original system are shown in Figure 5. The carbon intensity map reflects how clean the electricity of the system is. It can be noticed that Case 1, Case 2, and Case 3 all improve the cleaning level of the system to different degrees when compared to the original system. Case 2 does not plan for new wind turbines, but it does plan for energy storage, facilitating the accommodation of  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Case**} & \multicolumn{5}{c}{**Planning Results**} & \multirow{2}{*}{\
\begin{tabular}{c} **Total Fixed** \\ **Investment/10\$ USD** \\ \end{tabular} } & \multirow{2}{*}{
\begin{tabular}{c} **Carbon** \\ **Reduction Rate** \\ \end{tabular} } \\ \cline{2-2} \cline{4-6}  & **Capacity/MW** & & & & & \\ \hline Case 1 & 700 & 1 & 499 & 8 & 7.09 & 11.32\% \\ Case 2 & 0 & / & 557 & 8 & 4.48 & 1.06\% \\ Case 3 & 253 & 23 & 725 & 20 & 6.94 & 5.02\% \\ \hline \hline \end{tabular}
\end{table}
Table 7: Planning results of different cases in Scenario 1.  
Figure 7: Bus carbon intensities at optional ES locations before planning.  
existing wind power at buses 7 and 18 in the system. Case 1 and Case 3 have new wind turbines planned at bus 1 and bus 23, respectively. As a result, both drive down the carbon intensities of the surrounding buses.