## 5 Example Simulation and Analysis
### Results Analysis  
#### 5.4.1 Different Scheduling Scenes Analysis  
Energy storage power stations have a strong complementary ability to wind and solar power. Considering the uncertainty of wind power, the thermal power unit and the IDR are adjusted in the intraday scheduling, and the optimization scheduling results of each scheduling scene are analyzed. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Symbol** & **Parameter Value** & **Symbol** & **Parameter Value** \\ \hline \(N_{\text{pop}}\) & 100 & \(\gamma\) & 0.05 \\ \hline \(f_{1}\) & [0,100] & \(A_{0}\) & 0.25 \\ \hline \(r^{0}\) & 0.5 & \(\varepsilon\) & 0.95 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Improved BA parameter initialization settings. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Algorithm** & **Average/\$** & **Standard Deviation** & **Simulation Time** \\ \hline BA & 409,459.88 & 4.2719 & 2.04 \\ \hline GA & 396,102.31 & 3.2481 & 2.43 \\ \hline Improved BA & 389,024.49 & 1.9625 & 2.96 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Performance comparison of BA and improved BA. Figure 6: Start-stop cost and loss cost curves of thermal power units at different peak load adjustment depths. Table 4 shows the optimal scheduling costs in different system scenes. In the basic scene, there is no battery energy storage station and demand response, so thermal motor units are often in a deep peak condition and climb frequently. The thermal power unit cost is 262,140 dollars and the average adjustment cost is 81,735 dollars, and they are higher than in other cases. Compared to the day-ahead schedule in Table 3, the total system cost was reduced by $6,144.49. Case 2 contains the battery energy storage station, which relieves the peaking pressure of the thermal power unit to a certain extent, so the thermal power unit output cost and the intraday average adjustment cost are reduced compared with case1. In case3, the demand response virtual unit participates in the scheduling, which reduces the system load uncertainty during the day-ahead and intraday stage, and effectively avoids the impact of load fluctuation on system operation. In case4, the total system cost is 13,249 dollars less than the basic scene. Because this scene includes the carbon treatment cost, the output of thermal power units is limited to achieve low-carbon scheduling, and the data in the table shows that the amount of wind and light waste is reduced. Case5 integrates various factors, and the unit adjustment cost is reduced to $21,362 in the simulation results. Meanwhile, the total system cost is reduced by 14.82% compared with the basic scene. Therefore, the scheduling model proposed in this paper has significant advantages in reducing the two-stage average adjustment cost. According to the system load curve before and after demand response in Figure 7, the day-ahead electricity price guides residential users to change their electricity consumption behavior and intraday electricity price encourages industrial users to adjust the electricity time, which greatly reduces the peak-valley difference. It is economical and low-carbon to smooth the fluctuation of load, and the power supply pressure on the power side is eased during peak period, and it is obvious that the power interest rate is increased during the valley period. As is shown in Table 4, the adjustment cost and total system cost are reduced effectively with the demand response virtual units. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Cost/\$** & **Case1** & **Case2** & **Case3** & **Case4** & **Case5** \\ \hline Thermal & 262,140 & 257,343 & 147,004 & 237,406 & 139,512 \\ \hline Storage & - & 14,828 & - & - & 16,871 \\ \hline DR & - & - & 109118 & - & 118356 \\ \hline Adjustment & 81,735 & 60,138 & 42,031 & 73,021 & 21,362 \\ \hline Limit & 39,005 & 36,710 & 18,493 & 59,204 & 30,048 \\ \hline Total & 38,2880 & 369,019 & 316,646 & 369,631 & 326,149 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Optimal scheduling costs in different system scenarios.