## 5 Conclusions  
The rapid growth of wind power penetration in a distribution system poses challenges to the distribution system reliability. A reasonable energy storage control strategy, wind power control strategy and load demand side management can effectively alleviate the adverse effects caused by \begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**Location**} & \multicolumn{4}{c}{**SAIDI**} \\ \cline{2-5}  & \(P_{ddmax}\) = 600 kW & \(P_{ddmax}\) = 700 kW & \(P_{ddmax}\) = 800 kW & \(P_{ddmax}\) = 900 kW \\ \hline GS & 826 & 610 & 551 & 540 \\ QA & 629 & 440 & 366 & 369 \\ NTL & 601 & 392 & 339 & 334 \\ YA & 340 & 99 & 43 & 25 \\ \hline \hline \end{tabular}  
* GS: Guoshan; QA: Qingao; NTL: Niutouling; YA: Yunao.  
\end{table} 
Table 2: The installed \(P_{ddmax}\) of energy storage sited at different locations. 1  
Figure 14: Topographic map of Nanao (NA) Island. Figure 15: Single line diagram of the Nanao (NA) Island power system. the intermittence of wind power. Among these methods, a reasonable allocation of energy storage systems in a distribution system will effectively improve the distribution system reliability. The energy storage configuration affects the system operation reliability and maintenance. Therefore, not only the storage device owner focuses on the rational allocation of energy storage; for power system operators, the optimization allocation of energy storage is also important. This paper investigated the optimization allocation problem of an energy storage system in a distribution network. Based on existing energy storage allocation experiences, this paper presented a bi-level programming assessment model to solve the problem of optimal capacity and installation location allocation of energy storage under certain reliability requirements. The solution scheme based on the model is presented to determine the optimal installation location of the energy system under a certain system reliability. Compared with the configuration optimization method aiming to obtain the lowest cost of energy storage, the optimization method presented in this paper provides a practical solution to quantitatively evaluate the capacity and location optimization of an energy storage system. This method provides an intuitive basis for planners to allocate the location and capacity of energy storage. Case studies show that the different site of energy storage will yield different contributions to the system reliability, and the influence of different factors on the optimization results is analyzed by a sensitivity analysis. The main conclusions of this paper are as follows:  
First, an energy storage system can effectively improve distribution system reliability. This paper presented a novel optimization method for the capacity and installation site configuration of energy storage to provide a theoretical basis and practical method for the rational allocation of energy storage in a distribution network. Second, a search tree method was used to effectively solve the location selection problem in energy storage planning, and identified the installation position of energy storage. The algorithm greatly minimizes the calculation amount. Third, the sensitivity analysis of the proposed configuration model has been given, and this paper provides a reasonable and effective basis and a practical way to improve the system reliability in a distribution network. Remarkably, with installation at the end of the distribution network, the smallest energy storage capacity would be necessary to satisfy certain reliability requirements. A reasonable siting allocation of an energy storage system can effectively reduce the installed energy storage capacity. Future work will address the application of a bi-level programming method to the optimal allocation of the device types and parameters of the energy storage system. Moreover, the algorithm will also be studied to reduce the computational burden of optimization. This work was supported by the Key Project of Chinese National Programs for Research and Development (No.