# Simulation and Optimisation of Utility-Scale PV-Wind Systems with Pumped Hydro Storage
## 3 Computational Results and Discussion
### Sensitivity Analysis: Effect on Simulation Accuracy, Location, Electricity Price, and Costs
#### 3.4.1 Effect of Location  
Two new locations were considered for the optimisations (Table 6) to determine the effect of considering different locations (with different irradiation, temperatures, and wind speeds). Gran Canaria Island (Spain) (27.81\({}^{\circ}\) N, 15.43\({}^{\circ}\) W) is near the Tropic of Cancer and has a considerably greater irradiation and wind speed than Zaragoza. Sabinanigo, north of Huesca (Spain) (42.5\({}^{\circ}\) N, 0.36\({}^{\circ}\) W), had lower irradiation and wind speeds. Most locations in the country have irradiation and wind between the extremes of these locations.  
For the LSS systems, the results of the optimal system for each case are shown in Figure 24. For each type of project (no PHS, PHS, and PHS-B), there is one column for the previous section (Zaragoza location) and two other columns for the new locations (Gran Canaria and Sabinanigo). The left axis shows the rated power (MW) of the elements in the optimal combination, whereas the right axis shows the duration (h) and NPC (M EUR).  
\begin{table}
\begin{tabular}{l c c c} \hline \hline
**Location** & \multicolumn{2}{c}{**Zaragoza**} & \multicolumn{2}{c}{**Gran Canaria**} & \multicolumn{2}{c}{**Sabinanigo**} \\ \hline Latitude and longitude (\({}^{\circ}\)) & 41.66 N, 0.88 W & 27.81 N, 15.43 W & 42.50 N, 0.36 W \\ Optimal PV slope (\({}^{\circ}\)) & 35 & 15 & 35 \\ Average annual Irradiation over the optimal & 2013 & 2343 & 1977 \\ inclined surface (kWh/m\({}^{2}\)) & 15.45 & 20.01 & 10.75 \\ Average wind speed (m/s) at 53 m hub height & 6.96 & 8.31 & 5.6 \\ Wind speed Weibull form factor & 2.9 & 3.8 & 2.8 \\ \hline \hline \end{tabular}
\end{table}
Table 6: Resource data for the different locations.  
\begin{table}
\begin{tabular}{l c c c} \hline \hline
**Project Type** & **PGS—Optimal System** & \multicolumn{2}{c}{**PGS—A (Buy for**} & \multicolumn{2}{c}{**PGS—B (No Buy for**} \\  & **without PHS** & **Arbitrage)—Optimal** & **Arbitrage)—Optimal** \\ \hline PV energy (GWh/yr, average) & 3.417 & 5.125 & 5.125 \\ WT energy (GWh/yr, average) & 5.682 & 5.682 & 5.682 \\ Pump energy (GWh/yr, average) & - & 0.884 & 0.875 \\ Pump run hours/starts per year (average) & & 2039/691 & 2134/700 \\ Hydro turbine energy (GWh/yr, aver.) & - & 0.731 & 0.722 \\ Turbine run hours/starts per year (aver.) & - & 1650/624 & 1634/623 \\ E sold (GWh/yr, average) & 8.529 & 9.851 & 9.816 \\ E purchased (GWh/yr, average) & 0 & 0.042 & 0 \\ CAPEX (M EUR) & 4.96 & 6.72 & 6.72 \\ NPV (EUR) & 1.979 & 1.688 & 1.698 \\ LCOE (EUR/kWh) & 0.0536 & 0.061 & 0.0611 \\ \hline \hline \end{tabular}
\end{table}
Table 5: _Cont._We can see that PHS is not worthwhile in all cases; the optimal system without PHS has a lower NPC than the systems with PHS (type A or type B) for the three locations. The location with higher irradiation and wind speed (Gran Canaria) obtained the best results (negative NPC in all cases, i.e., the system obtained benefits after supplying a load). The optimal system at the location with the lowest irradiation and wind speed (Sabiannigo) had the highest NPC and did not include wind turbines.  
For PGS systems, the results of the optimal system found for each case are shown in Figure 25, which shows the right-axis NPV instead of the NPC. We can see that PHS is not worthwhile, as the optimal systems without PHS have a higher NPV (more profitable) than the corresponding systems with PHS.  
In both LSS and PGS, the differences between the optimal PHS type A and type B systems are low because the pump turbine sizes of the optimal systems are the minimum.