# Simulation and Optimisation of Utility-Scale PV-Wind Systems with Pumped Hydro Storage
## 4 Conclusions  
A new method for simulating and optimizing grid-connected utility-scale PV-wind-PHS systems was presented in this paper. To the best of our knowledge, this is the first time energy arbitrage has been considered for optimising renewable-PHS systems under electricity RTP schemes. The main conclusions of our study are listed below:  
1. For the three locations studied in Spain, the PHS is not worth the cost because the PV-wind system obtains better economic results for both LSS and PGS systems. This can be extrapolated to other locations in Spain and many other countries at similar latitudes. Even when using a hypothetical RTP electricity price with a considerably higher difference between the peaks and valleys, PHS is not worthwhile. The RTP affects the optimal size of the PV generator and wind turbine group (with the hypothetical RTP, PV is encouraged as it has a higher price in the central hours of the day); however, PHS is not competitive in both cases of RTP considering present PHS costs. Locations with low wind speeds affect the optimal size of the generators, not including wind turbines in the optimal size; however, PHS is not competitive in any location considered with the present PHS costs. 2. We found a wide range in which PHS CAPEX needed to compete with the system without storage, depending on the location and type of system (LSS or PGS). For example, in Zaragoza, a load-supply system would require 850 EUR/kW + 20 EUR/m\({}^{3}\) of PHS CAPEX to be competitive (which is not far from the present values), whereas a power-generating system would require 700 EUR/kW + 17.5 EUR/m\({}^{3}\). However, Gran Canaria (higher irradiation and wind speed) requires considerably lower values of PHS CAPEX to be competitive: 350 and 400 EUR/kW + 15 EUR/m\({}^{3}\). As the PHS cost has a wide range and high local dependency, we conclude that the renewable-PHS system with energy arbitrage under RTP could be profitable in many locations for both types of systems (LSS or PGS); however, every case is different and must be optimised individually. 3. In almost all optimisations, the optimal system with PHS includes the lowest pump-turbine size, as PHS is not worthwhile (too expensive), and therefore, the differences in the optimal solution for a PHS considering allowing (type A) or not (type B) the \begin{table}
\begin{tabular}{l c c c} \hline \hline  & **Results Obtained** & **Results after Changing:** & **Results after Changing:** \\  & **(\(\mathbf{P_{\%}}\) = 60\%)** & \(\mathbf{P_{\%}}\) = 40\%** & \(\mathbf{P_{\%}}\) = 80\% \\ \hline E. pump & & & \\ (GWh/yr) & 2.556 & 2.590 (+1.3\%) & 2.486 (\(-\)2.8\%) \\ E. turb & & & \\ (GWh/yr) & 2.061 & 2.077 (+0.8\%) & 2.015 (\(-\)2.3\%) \\ E. buy & & & \\ (GWh/yr) & 1.813 & 1.831(+1\%) & 1.792 (\(-\)1.2\%) \\ E. sell & & & \\ (GWh/yr) & 7.140 & 7.144 (+0.1\%) & 7.119 (\(-\)0.3\%) \\ NPC (M EUR) & 3.210 & 3.218 (+3.1\%) & 3.237 (+3.8\%) \\ \hline \hline \end{tabular}
\end{table} 
Table 11: Effect of the minimum hydro turbine load set point. Optimal LSS–A–547 EUR/kW + 2.7 EUR/m\({}^{3}\). system to buy electricity from the grid for arbitrage are very low. However, with low PHS CAPEX (the PHS being competitive), the optimal system includes a larger size of the pump-turbine, and the differences concerning Type A or B are greater, with a great influence on the pump, turbine, buy, and sell energies, and on the economic results (in LSS, NPC 13% higher in Type B). 4. Systems with small PHS sizes exhibit a low effect. However, in systems with high PHS size, the effect of the high/low limit set points for energy arbitrage is proven to be very important (increasing the arbitrage dead band by 0.04 EUR/kWh increases the NPC by 7.5%). The optimal set point for the minimum hydro turbine load obtained in all optimisations is a high value (60-80% of the rated power) to improve hydro turbine efficiency, and the effect of varying it by 20% over the optimal implies a 3% increase in NPC.