## 5 Case Study
### Analysis of Day-Ahead Optimization Scheduling Strategies for Different Types of Pumped Storage  
To assess the flexibility of ternary pumped storage and explore the effects of the various types of PS on the day-ahead optimization scheduling of the power system, this paper considers different combinations of FS-PSUs, VS-PSUs, and T-PSUs, detailed in eight configuration schemes as outlined in Table 4. Among them, schemes 2 to 5 are the various combinations of FS-PSUs and VS-PSUs, which belong to the previous studies. Schemes 6 to 8 are the various combinations of T-PSUs proposed in this paper. Under different configuration schemes, the total capacity of the pumped storage remains the same (i.e., 360 MW). The day-ahead optimization dispatch outcomes for such wind-thermal-pumped storage bundled systems (under various configurations: without pumped storage, with only FS-PSUs, with only VS-PSUs, and with only T-PSUs) are shown in Figures 3-6. Among them, \"P1\", \"P2\", \"P3\", and \"P4\" represent the pumps of the four units in the PS, while \"G1\", \"G2\", \"G3\", and \"G4\" represent their turbines. \"P_line\" represents the power of the transmission channel, and \"energy_PS\" refers to the electricity energy stored by the PS. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Configuration Schemes** & **Combination Approach** & **Capacity of FS-PSUs/MW** & **Capacity of VS-PSUs/MW** & **Capacity of T-PSUs/MW** \\ \hline
1 & No PS & - & - & - \\
2 & PS with only FS-PSUs & 4 \(\times\) 90 & - & - \\
3 & Hybrid PS with FS-PSUs and VS-PSUs & 3 \(\times\) 90 & 1 \(\times\) 90 & - \\
4 & Hybrid PS with FS-PSUs and VS-PSUs & 2 \(\times\) 90 & 2 \(\times\) 90 & - \\
5 & PS with only VS-PSUs & - & 4 \(\times\) 90 & - \\
6 & Hybrid PS with FS-PSUs and T-PSUs & 3 \(\times\) 90 & - & 1 \(\times\) 90 \\
7 & Hybrid PS with FS-PSUs and T-PSUs & 2 \(\times\) 90 & - & 2 \(\times\) 90 \\
8 & PS with only T-PSUs & - & - & 4 \(\times\) 90 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Pumped storage configuration schemes. Figure 3: Day-ahead optimization scheduling results of wind-thermal bundled system. \begin{table}
\begin{tabular}{c c c} \hline \hline
**Periods** & **Intervals** & **Price/(CNY/kW-h)** \\ \hline Peak period & 10:00–15:00, 18:00–21:00 & 1.2893 \\ Flat period & 7:00–10:00, 15:00–18:00, 21:00–23:00 & 0.8731 \\ Valley period & 23:00–7:00 & 0.4570 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Time-of-use electricity prices in a certain area. (1) Scheduling strategies analysis in configuration scheme 1. Figure 2 shows that wind power has an evident anti-peaking characteristic, rising when the load falls in 2:00-4:00 and 19:00-24:00, and falling when the load rises in 9:00-12:00. This characteristic can intensify the peak-to-valley difference of the net load curve. Figure 3 demonstrates that T1 undergoes large volatilities, ranging from a minimum of 228 MW to a maximum of 570 MW, and then dropping back to 228 MW. The peak-valley difference of thermal power output in a day is as high as 342 MW. T4 has similar characteristics. While the peak regulation of thermal power satisfies the balance requirements of system, it also subjects the thermal power to significant adjustment pressures, thus affecting its smooth operation. (2) Scheduling strategies analysis in configuration schemes 2, 5 and 8. Figures 4-6 show that with PS in the system, it pumps during low-load hours from 1:00 to 9:00, storing excess wind power, and generates during peak hours from 12:00 to 20:00. Figure 4: Day-ahead optimization scheduling results of wind-thermal-pumped storage bundled system with only FS-PSUs. Figure 5: Day-ahead optimization scheduling results of wind-thermal-pumped storage bundled system with only VS-PSUs. Figure 6: Day-ahead optimization scheduling results of wind-thermal-pumped storage bundled system with only T-PSUs. The dispatch results in Figure 6 show that the power output of T1 increases from 231 MW to 513 MW and then drops to 355 MW throughout the whole day.