# Assessing the Impact of an EV Battery Swapping Station on the Reliability of Distribution Systems
In [11], a two-layer optimization model that simultaneously determines dynamic pricing policy for the system operator and demand response strategies for the EV parking lots was built. It proved that dynamic pricing with demand response from EVs can lower the daily average consumer cost. [12] presents a novel mechanism to calculate EV charging prices using individualized energy consumption patterns of EVs in each region to get fair cost distribution with high user satisfaction and improve the grid economy. In the mentioned papers, significant research efforts have been made for the investigation of the EV role in future power systems. However, for most of these existing studies, the corresponding studies were implemented based on the assumption that EV units were integrated and interacted with the power system via charging stations. Nevertheless, in practice, the energy demand of EVs could be met by different types of charging infrastructures, among which the battery swapping station (BSS) can be another important option. In contrast to the conventional fast-charging stations, the BSS removes the power battery of the vehicle through a quick replacement device and immediately replaces it with another power battery that meets the requirements [13]. The user can drive the electric car away in a short time, and the replaced power battery is left in the BSS to complete the charging process. Therefore, in the battery swapping mode, the user can regain the required power through quick battery replacement without having to stay for a long time, which has higher convenience [14]. At the same time, compared with the traditional charging station model, BSS operators can flexibly arrange battery charging and discharging plans to deeply participate in the power market and achieve profitability [15]. For the power grid, model-based management of the BSS load is conducive to peak-shaving and valley-filling of the power grid, reducing the adverse effects on the efficient operation of the power grid caused by the random charging behavior of EV users and improving the power supply reliability and economy of the distribution system. In spite of considerable focus given to the potential value of the BSS in the future power systems, barely any studies have investigated such an issue from the grid's point of view so far, except for [15] and [16]. In [15], an optimal scheduling model to minimize the operation cost of a grid-connected micro-grid (MG) considering the accommodation of distributed generation (DG) and BSS is proposed. The effects of var compensators, optimal BSS scheduling, and reactive power costs on active/reactive power dispatch and MG operation cost are comprehensively investigated. In [16], a dynamic operation model of BSSs in an electricity market is developed. The model is formulated based on the short-term battery management and energy bidding strategy in electricity market. The results show that the BSS makes decisions in a market environment through tracing the number of batteries in different kinds of states, and it acquires additional revenue by responding actively to the price fluctuation in the electricity market. However, in the literature described above, barely any studies were dedicated for exploring the implication of BSSs on system reliability. In a real-world scenario, the BSS with bi-directional chargers can work as an alternative supply source and provide capacity support to the grid during emergencies by extracting energy from its replaced EV batteries. Therefore, this could mitigate the risk of loss-of-load, where the risk of loss-of-load refers to the economic loss caused by the interruption of power supply due to the failures of system components. It reflects both the possibility and severity of the power interruption and can be derived as the product of system failure probability, loss-of-load at the demand side, and the economic value of lost load. The economic value of lost load is mainly related to the duration of the power outage and the type of customers at the demand side.