# Risk-Based Virtual Power Plant Implementation Strategy for Smart Energy Communities
## 4 Results
### Effects of Demand  
The resources for implementing a VPP change according to the characteristics of demand. In the VPP implementation servicing the demand of a commercial SEC, PV  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Method Resource** & **P0** & **P1** & **P1** & **P1** & **P2** & **P2** & **P2** \\  & **(\(\gamma\)=0.1)** & **(\(\gamma\)=0.5)** & **(\(\gamma\)=1)** & **(\(\gamma\)=0.1)** & **(\(\gamma\)=0.5)** & **(\(\gamma\)=1)** \\ \hline PV1 & 0 & 0 & 0 & 0 & 0 & 0 \\ PV2 & 740 & 757 & 852 & 807 & 410 & 515 & 535 \\ PV3 & 0 & 0 & 0 & 0 & 0 & 0 \\ PV4 & 240 & 0 & 128 & 196 & 45 & 170 & 190 \\ PV5 & 0 & 0 & 0 & 0 & 0 & 0 \\ PV6 & 0 & 0 & 0 & 0 & 0 & 0 \\ PV7 & 0 & 0 & 0 & 0 & 0 & 0 \\ PV8 & 0 & 0 & 0 & 24 & 0 & 0 & 0 \\ PV9 & 0 & 0 & 0 & 0 & 0 & 0 \\ PV10 & 247 & 0 & 0 & 0 & 0 & 0 \\ Wind1 & 224 & 154 & 207 & 212 & 0 & 0 \\ Wind2 & 28 & 241 & 45 & 45 & 565 & 565 & 565 \\ Wind3 & 0 & 0 & 0 & 0 & 0 & 0 \\ Wind4 & 0 & 0 & 0 & 0 & 0 & 0 \\ Wind5 & 0 & 0 & 0 & 0 & 0 & 0 \\ Wind6 & 395 & 281 & 363 & 385 & 35 & 180 & 205 \\ Wind7 & 148 & 0 & 155 & 146 & 0 & 0 & 0 \\ Wind8 & 0 & 0 & 0 & 0 & 0 & 0 \\ Wind9 & 0 & 0 & 0 & 0 & 0 & 0 \\ Wind10 & 0 & 0 & 0 & 0 & 0 & 0 \\ \hline PV total & 1227 & 757 & 980 & 1027 & 455 & 685 & 725 \\ Wind & 795 & 676 & 770 & 788 & 600 & 745 & 770 \\ \hline \hline \end{tabular}
\end{table}
Table 1: VPP implementation results for a commercial SEC.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Method Resource** & **P0** & **P1** & **P1** & **P1** & **P2** & **P2** & **P2** \\  & **(\(\gamma\)=0.1)** & **(\(\gamma\)=0.5)** & **(\(\gamma\)=1)** & **(\(\gamma\)=0.1)** & **(\(\gamma\)=0.5)** & **(\(\gamma\)=1)** \\ \hline PV1 & 0 & 0 & 0 & 0 & 0 & 0 \\ PV2 & 0 & 0 & 0 & 0 & 0 & 0 \\ PV3 & 0 & 0 & 0 & 0 & 0 & 0 \\ PV4 & 0 & 0 & 0 & 0 & 0 & 0 \\ PV5 & 0 & 0 & 0 & 0 & 0 & 0 \\ PV6 & 0 & 0 & 0 & 0 & 0 & 0 \\ PV7 & 0 & 0 & 0 & 0 & 0 & 0 \\ PV8 & 0 & 0 & 0 & 0 & 0 & 0 \\ PV9 & 0 & 0 & 0 & 0 & 0 & 0 \\ Wind1 & 205 & 161 & 195 & 204 & 75 & 80 & 80 \\ Wind2 & 41 & 145 & 70 & 51 & 250 & 250 & 250 \\ Wind3 & 0 & 0 & 0 & 0 & 0 & 0 \\ Wind4 & 0 & 24 & 0 & 0 & 0 & 0 & 0 \\ Wind5 & 0 & 0 & 0 & 0 & 0 & 0 \\ Wind6 & 117 & 38 & 103 & 108 & 0 & 20 & 25 \\ Wind7 & 89 & 2 & 65 & 81 & 0 & 0 & 0 \\ Wind8 & 0 & 0 & 0 & 0 & 0 & 0 \\ Wind9 & 0 & 0 & 0 & 0 & 0 & 0 \\ Wind10 & 0 & 0 & 0 & 0 & 0 & 0 \\ \hline PV total & 0 & 0 & 0 & 0 & 0 & 0 & 0 \\ Wind & 452 & 370 & 433 & 444 & 325 & 350 & 355 \\ \hline \hline \end{tabular}
\end{table}
Table 2: VPP implementation results for a residential SEC.  
resources were largely utilized, and wind resources were compensated, as shown in Table 1. To check Pearson's linear correlation coefficient (PLCC) [35], the demand of the commercial SEC and the PV resources had a high correlation coefficient, as shown in Table 3. Among them, the PV2 and PV4 resources with the highest and the second highest correlation coefficients were used for the VPP implementation serving the demand of the commercial SEC. For wind resources, Wind2 and Wind7, negatively correlated to the demand of the commercial SEC, were used in addition to Wind1 and Wind6, which had positive correlations with the demand of the commercial SEC. In particular, in the results for **P2**, Wind2, which had low correlation with the existing constituent resources, was used more compared to the results for other methods.  
As shown in Table 3, the PCCC between the demand of the residential SEC and the PV resources was negative. Therefore, the VPP was implemented only using wind resources to serve the demand of the residential SEC, as shown in Table 2. Similar to the case of the commercial SEC, Wind1, which had the highest correlation with demand, was mainly used to serve the demand of the residential SEC.