## 3 Methodology  
As previously mentioned, SAM was used to simulate the solar field and the irradiation received by the receiver. This simulation employed the model developed by [35], which was validated using annual production data from the Gemasolar plant [62]. The data on incident irradiation at the receiver were subsequently processed to serve as input for the design of the remaining sections of the solar thermal power plant. These sections included the receiver, thermal energy storage system, steam generation, and power production. For this design, intermediate efficiency values from Tables 4 and 7 were applied. A summary of the assumed efficiencies is provided in Table 10.  
The control strategy and operational framework of plant production is based on the system's technical limitations and the previously described constraints. The objective is to determine the amount of energy produced during a typical meteorological year (TMY). The plant's production strategy follows the operational modes commonly employed in commercial CSP tower plants, as described in [29; 63]. Figure 3 illustrates a typical operational diagram for this type of plant:  
* Storage Mode: The Rankine cycle is powered, and the thermal storage system is charged when the storage level is between the defined minimum and maximum. * Non-Storage Mode: The solar field only supplies energy to operate the Rankine cycle at nominal capacity, without charging storage, as it is already full. * Discharge Mode: During periods without irradiation (nighttime or cloudy weather), stored thermal energy powers the Rankine cycle, provided storage exceeds the minimum threshold. * Disconnected Mode: No energy is produced or stored due to lack of irradiation or operational decisions by the plant. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Area** & **Molten Salts (\%)** & **DPS (\%)** & **Variation (\%)** \\ \hline Receiver & 88.5 & 79.5 & 9.0 \\ Heat exchanger & 85.0 & 96.0 & \(-11.0\) \\ Power block & 41.2 & 45.4 & \(-4.2\) \\ Storage & Constant & Constant & 0 \\ Electricity-to-heat & 95.1 & 91.3 & 3.8 \\ \hline \hline \end{tabular}
\end{table} 
Table 10: Efficiencies comparison between molten salts scenarios vs. DPS scenarios. The strategy was implemented using three operational states. A flowchart illustrating the general operation of the plant is presented in Figure 4.  
* Plant Offline: When the plant is offline, the control algorithm evaluates the storage system's charge level. If feasible, it initiates the progressive startup sequence. * Plant Starting/Shutting Down: The algorithm assesses whether the charge level is sufficient to continue the startup sequence and, if so, the system progressively increases power until the nominal level is reached, simulating a warm start within one hour. If the system is in the process of shutting down, it also checks whether this can be reversed under the same condition. If the charge level is insufficient, the shutdown proceeds as planned. * Plant Online: Depending on the charge level, the control algorithm decides to maintain nominal power production or initiate shutdown with a gradual reduction in power. The thermal storage system is modeled with the following equations: \[STO(k)=STO(k-1)+SUN(k)-LOSS(k)\quad\text{ \sc Scenario I and III}\] (3) \[STO(k)=STO(k-1)+SUN(k)+SURP(k)-LOSS(k)\quad\text{ \sc Scenario II and IV}\] (4) where SUN represents the incident irradiation on the receiver, as defined by the SAM simulation based on the model in [35]; LOSS is a fixed value accounting for tank dimensions (Table 2) and experimental area-specific heat losses determined by [65]; and SURP denotes the electrical surpluses, defined as follows: \[SURP(k)=\eta_{cartot}\cdot\left(SURP(k)_{wind}+SURP(k)_{phot}+SURP(k)_{therm}\right)\] (5) where \(\eta_{\text{cartot}}\) is the efficiency for electricity-to-heat energy conversion, with values provided in Tables 8 and 9. When SURP(k) \(\geq\) 15 MW, it is capped at 15 MW, while for SURP(k) \(<\) 15 MW, the equation above applies.