# Dispatchable Substation for Operation and Control of Renewable Energy Resources
## 3 Operation of Dispatchable Substation with Renewable Generator Mix
### ESS Configuration Considering RES Type and Forecast Accuracy  
A difference exists in the forecast accuracy and generation pattern between the wind and PV generators. It is important for the DSS to analyze the characteristics of interconnected renewable generators with a variable combination of PV and wind capacity. The combination of the generation mix is listed in Table 1 for a 30-MW substation connection. The forecast and measured data were obtained from a weather station near Rotterdam, Netherlands. For each case, solar irradiance and wind speed are adopted for the given capacity value to calculate the difference between the generation output of the forecast and the measured data. Figure 6 shows the deviation of the measured value from the forecast value for a given data of one year. The graph shows that case 1 (wind plants only) recorded the most frequent deviation from the forecast value. Except for the record of the 1-MW forecast error, the most stable generation mix with the least forecast error is seen for case 3, which has an equal proportion of PV and wind generator capacity. This is because the correlation between wind forecast error and the PV forecast error is insignificant. \begin{table}
\begin{tabular}{l c c c} \hline \hline  & **Wind [MW]** & **PV [MW]** & **Total Generation Per Year [GWh]** \\ \hline Case 1 & 30 & 0 & 255.9 \\ \hline Case 2 & 22.5 & 7.5 & 228.6 \\ \hline Case 3 & 15 & 15 & 201.3 \\ \hline Case 4 & 7.5 & 22.5 & 174.0 \\ \hline Case 5 & 0 & 30 & 146.7 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Generation mix for forecast error analysis. Figure 5: Operation of a dispatchable substation in the charge mode. When the DNE limit set by the TSO is assumed to be 10% for the rated capacity of the renewable generators, the ESS in the DSS must actively compensate for the generation that deviates from the forecast values by more than 3 MW. For an operation data of one year, more than 365 h of violation occur for case 1, whereas only 45 h of predictions are missed for case 3. With a DSS, it is expected that the forecast error beyond the DNE limit can be significantly reduced. With the 0.5-MW ESS in the substation, the number of violations can be reduced by up to 50%. Although forecast errors for wind turbines are recorded more frequently than those for PV systems (compare case 1 and case 5), the total yearly generation of wind turbines is greater. Thus, a large wind-farm with DSS requires more ESS's capacity than DSS with PV generators only. A precise assessment of the ESS's capacity should be performed by comparing the capital cost of facilities and the economic benefits with ESS installation. The joint distribution of the measured and forecasted generation output is shown in Figure 7. The correlation distribution within the DNE limit is depicted by a blue circle, and the mis-predicted data are depicted by an orange cross. The kernel distribution of the histogram of each data point can be found on each axis. Figure 6: Cumulative hours of forecast error for each case in Table 1.  
Figure 7: Joint distribution of measured and forecast generation output for case 2 in Table 1.  
The blue line represents the kernel distribution of cases that less than 3 MW forecast error occurred while the orange line is the kernel distribution of cases with more than 3 MW forecast error. The distribution on x-axis is corresponding to the kernel distribution that is sorted by measured values. Likewise, the distribution on y axis is sorted by forecast values. Normally, the distribution of wind generation can be described by a \"Weibull distribution\". The data with more than 3 MW prediction errors have different distributions compared with normal cases that have a Weibull distribution. Furthermore, 80% of error cases are concentrated between 7.31 MW and 14.71 MW. It can be concluded from the joint distribution that the operation of the ESS in the DSS must be more active when the forecasted generation is expected to exist within the 80% area.