## 5 Simulation and Discussion
### Intraday MPC Rolling Optimization Simulation Analysis
#### 5.3.4 Intraday Scheduling DHB Strategy Evaluation  
The results for the three cases are shown in Table 10. Comparing Case A and Case B, it is evident that further adjusting the hydrogen blending ratio \(r\) during the intraday period leads to a decrease in the upper-layer and lower-layer tracking error based on CHB by 4.25% and 2.3%, respectively, indicating that this strategy enables MPC to track the targets more accurately. However, this strategy is accompanied by a certain increase in adjustment cost. In Case B, although the total adjustment cost increased by 0.84% compared to Case A, the improvement in tracking precision due to the adjustment of the blending ratio requires a balance between controlling error and controlling cost. For better tracking performance, further dynamic adjustment of the hydrogen blending ratio during the day is an ideal choice, with the slight increase in total adjustment cost being acceptable. Compared to Case A, although CHB exhibits some advantages in the upper-layer tracking error metric, the transmission of coupling parameters between layers leads to an increase in the lower-layer tracking error due to excessive tracking in the upper layer, indirectly elevating the total tracking error. In contrast, Case C, when adjusting the hydrogen blending ratio, can mitigate lower-layer fluctuations, achieving a superior lower-layer tracking performance, with a reduction in the lower-layer tracking error of 2.43%. Considering the shorter timescale and greater uncertainty fluctuations in the lower-layer model, this indicates that THB demonstrates better intraday tracking performance under these circumstances.This result also corroborates that the THB strategy aligns more closely with the hierarchical control architecture of practical systems. The upper layer (operating on a longer timescale) is responsible for formulating relatively stable operational plans. In comparison, the lower layer (operating on a shorter timescale) focuses on rapid fluctuation suppression and precise tracking. The comparison of cost contrasts with the trends in tracking error. In terms of cost optimization, CHB performs better in the overall economy, particularly in upper-layer adjustment costs, while the lower-layer economy is still inferior to THB. Therefore, when emphasizing long timescale scheduling issues, the CHB strategy achieves a good balance between tracking precision and economic performance, ensuring that the system operates efficiently. For short timescale power scheduling issues, THB's advantages are more prominent. For the overall IES, CHB is more suitable for long-term scheduling scenarios with higher economic requirements and sufficient computational resources, ensuring tracking performance within a certain range. In contrast, THB is more suited to stabilizing the tracking of day-ahead scheduling strategies, especially for scenarios that emphasize scheduling stability and operational convenience. A comparison between Case D (using real-world data) and Case C (using simulated data) reveals that the metrics, while showing some variation, are largely comparable. This is attributed to the fact that although the actual fluctuation patterns of renewable generation and various energy loads differ between the cases, the forecast error levels of the data employed are similar. These results demonstrate the proposed model's robustness in the \begin{table}
\begin{tabular}{l c c c c c c c} \hline \hline \multirow{2}{*}{**Case**} & \multirow{2}{*}{**Average Solving Time (s)**} & \multicolumn{3}{c}{**Tracking Error (kWh)**} & \multicolumn{3}{c}{**Adjustment Cost (CNY)**} \\ \cline{3-8}  & & **Upper** & **Lower** & **Total** & **Upper** & **Lower** & **Total** \\ \hline A & 0.324 & 3977.68 & 2318.28 & 6295.97 & 1238.583 & 1850.858 & 3089.441 \\ B & 0.385 & 3908.12 & 2313.26 & 6221.39 & 1269.038 & 1846.133 & 3115.171 \\ C & 0.338 & 4002.25 & 2261.97 & 6264.23 & 1340.818 & 1815.600 & 3156.418 \\ D & 0.331 & 3876.53 & 2332.52 & 6209.05 & 1339.676 & 1851.996 & 3191.672 \\ \hline \hline \end{tabular}
\end{table}