# Assessing the Impact of an EV Battery Swapping Station on the Reliability of Distribution Systems
## 7 Conclusions  
This paper studies the potential benefits of BSS on the power supply reliability of a distribution network. We develop an empirical model with an explicit consideration of BSS characteristics for describing the energy demand of EVs and their resultant AGC, which can serve as a backup source in case of an outage in distribution systems. Then, on this basis, a quantitative method to quantify the effect of a grid-connected BSS on distribution system reliability is proposed, which provides a practical tool to analyze the potential value of BSS resources in future distribution systems compared with most  
Figure 11: Convergence curves by using different sampling methods. \begin{table}
\begin{tabular}{c c c} \hline \hline
**Sampling Method** & **SRS** & **LHS** \\ \hline EV flow & 0.0524 & 0.0100 \\ Initial SOC & 0.0663 & 0.0098 \\ Component failure state & 0.0110 & 0.0098 \\ \hline \hline \end{tabular}
\end{table} 
Table 8: Correlation of sample rows in different sampling methods. of extant studies that only focus on an EV fast charging paradigm. We also adopt LHS-based sequential simulation to explicitly capture the uncertainties associated with EV users' behaviors, improve the result accuracy, and accelerate the convergence of the evaluation compared to traditional SMCS based on SRS. The results of the numerical study show that:  
BSS without V2G function will increase the loading level of the distribution network. When the grid is encountered with contingencies (line failures), the distribution network will suffer from a larger power supply shortage, which will reduce the reliability of the distribution network. However, as the BSS with V2G capability can be used as a backup energy source to reverse power to the grid during these emergencies, it could be helpful to reduce the power shortage and improve the reliability of power supply, if utilized appropriately. The charging strategy based on the peak-valley pricing scheme could have a positive effect on the peak-shaving and valley-filling of distribution grids. However, as for disorderly charging, due to the overlapping effect that exists between the peak power consumption and the peak BSS charging load, it could bring serious peak load, aggravate the peak-to-valley difference, and finally impact the smooth operation of the power grid. So, when the grid is involved in a failure event, it will often suffer from a greater power supply shortage, and the reliability will be further reduced. As a stratified sampling method, LHS covers a wider range under the same sampling times, and the row correlation between samples is smaller, so LHS-based sequential simulation is more accurate than SMCS and has a faster convergence speed. Our research still needs improvement in some aspects. In future research, the problem of road congestion near BSSs should be considered, which reflects the interaction between BSSs, distribution networks, road networks, and EV users. What is more, although the swapping time is very short, assuming battery swapping requires no time is still risky. We can use a smaller time scale or adopt queuing theory to fully consider this factor. Finally, the charging strategy we used can improve the reliability of the distribution system and provide economic benefits at the same time, but it is still not the optimal strategy. Designing a better charging strategy that can fully exploit the reliability enhancement and economic benefits of BSSs is also an interesting task. As an intelligent power component, the BSS will play an increasingly important role in large-scale EV access to the grid and improve the reliability of the distribution network. Hopefully, the outcomes of this research can provide some reference value for the BSS planning, construction, and operation of distribution networks in the context of future smart cities. Conceptualization, B.Z. and Y.L. ([PERSON]); methodology, Y.L. ([PERSON]); software, Y.L. ([PERSON]); validation, B.Z. and Y.L. ([PERSON]); formal analysis, B.Z. ; investigation, Y.L. ([PERSON]); resources, B.Z.