## 4 Numerical Results
### Simulation Results
It is higher than that for scene B, indicating that the planning strategy of DG, having more connection nodes and more dispersed distribution, can help to improve the flexibility of the distribution network. Because of the distinct renewable energy consumption requirements at different stages in different regions, it is necessary to carry out sensitivity analysis for abandonment rates of PV and WF in the proposed optimization model. Table 5 presents the sensitivity analysis results considering abandonment rates of PV and WF, namely 10% (Case 1), 30% (Case 2), and 50% (Case 3), which include the fitness of each objective function and the total DG accommodation capacity of the optimal compromise solution. It can be seen from Table 5 that with the increase of permissible abandonment rate, the total accommodation capacity of DG increases after optimization. At peak load stages, the distribution network can use more renewable energy, and the power transmission pressure of the lines in the distribution network is reduced. Eventually, the line capacity margin index increases from 56.5% to 57.1%. Take scenario 1 and scenario 12 as examples. Figure 8 shows the voltages of node 41, considering different abandonment rates for all dispatching periods. Scenario 1 is composed of PV scenario 1 and WF scenario 1, while complex scenario 12 is composed of PV scenario 4 and WF scenario 3. When the permissible abandonment rate is 50%, the total accommodation capacity of DG reaches the maximum value of 31.6 MW. Under complex scenario 1, the high output power of WF at dispatching periods 3 and 4, which are load peak stages, can provide adequate voltage support. The bigger accommodation capacity of WF at node 41 will cause higher nodal voltage amplitude, even exceeding the rated voltage. Under scenario 12, the WF output power at load peak stages is lowest and the output level of PV is also low, which makes it difficult to support the nodal voltage of node 41 at a distance. In case 3, although the total accommodation capacity of DG is maximal, the voltages of node 41 for dispatching periods 3 and 4 are 19.9961 kV and 19.9964 kV, respectively, which are still lower than the rated voltage. Figure 9 represents the voltage of node 5 under all scenarios. It shows that the magnitude of nodal voltage is influenced by the types of scenarios. Under scenario 10, the power of PV, whose output characteristic is consistent with that of load, is the largest, while the power of WF, whose output characteristic is different to that of load, is the smallest. Hence, the value of the nodal voltage at each \begin{table}
\begin{tabular}{c c c} \hline \hline  & **Scene A** & **Scene B** \\ \hline Daily energy supply of DG & 476.8 MW-h & 282.0 MW-h \\ Voltage amplitude deviation & 0.347 & 0.257 \\ Line capacity margin & 58.1\% & 58.7\% \\ Total accommodation capacity of DG & 78.9 MW & 38.2 MW \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Optimal compromise solutions under two scenes. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Permissible Abandonment Rate** & **Case 1 (10\%)** & **Case 2 (30\%)** & **Case 3 (50\%)** \\ \hline Daily energy supply of DG & 532.5 MW-h & 604.0 MW-h & 644.4 MW-h \\ Voltage amplitude deviation & 0.0933 & 0.0965 & 0.1027 \\ Line capacity margin & 56.5\% & 57.0\% & 57.1\% \\ Total accommodation capacity of DG & 20.5 MW & 27.7 MW & 31.6 MW \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Sensitivity analysis results considering different abandonment rates.