# Distributed Generation Cluster Division Method Considering Frequency Regulation Response Speed
## 5 Case Study
### Actual System Validation  
In this paper, a power distribution system in China is analyzed to verify the effectiveness of the proposed cluster division method. The 35 kV network of the distribution system is the object of division, and each 35 kV station is a node. There are 43 nodes in the network, and the nodes containing renewable energy are all over the system, mainly PV and some hydroelectric under the bus of nodes 40 and 45. The access forms of PV nodes are mainly household rooftop PV panels and village collective small-scale PV power stations in medium- and low-voltage distribution networks. The locations of the nodes that exhibit load characteristics are more centrally located, mainly at nodes subordinate to the 17-, 24-, and 30-node buses. The available power conditioning options in the system are located at node 53 and include energy storage devices (total power of 4 MW, total capacity of 20 MW\(\cdot\)h) and partially controllable loads. To simplify the calculations, the real-time controllable loads of the nodes are calculated with a constant value of 3 MW. The network topology is shown in Figure 8.  
The genetic algorithm parameter settings are the same as in the previous section. Since the renewable energy in the actual distribution system is mainly PV, the daily power output characteristics in the same area are somewhat similar; thus, the same typical (10:00 a.m.) power data of each node are selected for cluster division analysis.  
In order to verify the effectiveness of the method proposed in this paper, scheduling simulations are carried out based on the results of different cluster divisions to calculate the net power that can be used for frequency regulation within the clusters, and then the differences in dissipation capacity of the different methods are compared. Scenario A does not adopt the division scheme but adopts the method of nearby source-load complementary power scheduling; scenario B adopts the scheme of [PERSON] et al. (2016) for the division and carries out power scheduling within small clusters after division; and scenario C is based on the cluster results obtained by the improved comprehensive performance index proposed in this paper and carries out power scheduling in the same way as scenario B. The results of cluster division are shown in Figures 9 and 10. Since the analysis of the theoretical data of the indexes was conducted in the previous section, this section does not include explanations and demonstrations.  
Figure 8: Topology diagram of actual distribution system structure.  
The enhancement of cluster frequency regulation depends on the power regulation capability of the nodes, so the analysis focuses on clusters containing nodes with power regulation capability. A small cluster division is selected to analyze the change in net power of the source load over a 24 h period.  
From Figure 11, it can be seen that the power balance with cluster division is better after the division, showing that the net system power is greater in the 24 h time scale. Compared with scheme B, the proposed scheme more fully takes into account the power coordination between renewable energy sources, and therefore can make full use of the energy storage and responsive load regulation capability. This is shown in Figure 4, where the area of power is larger, and Table 3, which indicates that the whole system has a higher surplus of power, and thus has greater frequency regulation potential.  
Figure 11: Net power of related clusters in certain periods.  
Figure 10: Division results under scheme C.  
Figure 9: Division results under scheme B.