New energy electric vehicles are a sustainable mode of transportation with development potential because they are likely to reduce carbon dioxide emissions and air pollution, mitigate risks associated with oil resources, and be able to use renewable energy sources such as wind energy to achieve sustainability. The battery swapping behavior of new energy vehicles is the most important manifestation of its difference from the traditional fuel vehicle operation mode. However, there is no research on the impact of electric taxi swapping demand on the operation of power grid swapping stations. To tackle this issue, a novel approach is proposed in this paper. Specifically, we use data mining techniques to perform big data analysis of GPS data from fuel taxis operating to derive the operation patterns of existing taxis. The operation pattern is then used as the basis for the operation of electric taxis to obtain the impact of different switching demands on the operation of distribution network switching stations. This paper has an effective guiding role in the planning and operation of power exchange station construction for power companies. The method proposed in this paper has the potential to provide a reference strategy for the construction and operation of battery replacement sites for power companies, enabling them to reduce the cost of operating a replacement station while ensuring the quality of service at the station.