## 1 Introduction
### Research Literature Review  
The incorporation of battery swapping stations into the power grid presents a promising solution to tackle the challenges associated with EV charging infrastructure. However, ensuring the optimal planning of these stations is paramount, particularly when considering dynamic power distribution network reconfiguration and technical intricacies of the power grid, to ensure their efficient operation. This review critically assesses the recent literature pertaining to the optimal planning of battery swapping stations, with a specific emphasis on their integration with dynamic power distribution network reconfiguration and the technical considerations inherent in the power grid. This review scrutinizes various methodologies, identifies challenges, explores opportunities, and delineates potential future research directions in this rapidly evolving domain. Reference [1] focuses on determining the ideal size and location of battery swapping stations while accounting for power system reliability and fluctuations in load. While it underscores the necessity for robust infrastructure planning to guarantee the dependable operation of battery swapping stations within the power grid, it may fall short in fully incorporating dynamic power distribution network reconfiguration or offering comprehensive insights into technical grid aspects, potentially undermining the robustness of the planning approach. Reference [2] delves into the optimal allocation of battery swapping stations, with a keen eye on system reliability. It underscores the importance of strategically siting these stations to bolster the overall reliability of the power distribution network. Nevertheless, it may lack a comprehensive integration of dynamic power distribution network reconfiguration or a thorough consideration of technical grid aspects, potentially leading to less effective planning outcomes. Reference [3] employs particle swarm optimization (PSO) to ascertain the optimal placement and size of battery swapping stations. By leveraging advanced optimization techniques, the study endeavors to enhance the efficiency and efficacy of battery swapping station planning. However, it may not fully integrate dynamic power distribution network reconfiguration or comprehensively address technical grid aspects, potentially diminishing the planning approach's effectiveness. Reference [4] places significant emphasis on user convenience as a pivotal factor in determining the optimal placement of battery swapping stations. The research endeavors to augment the accessibility and usability of battery swapping infrastructure to encourage the widespread adoption of electric vehicles. Despite its focus on user-centric considerations, it may lack a holistic integration of dynamic power distribution network reconfiguration or a comprehensive examination of technical grid aspects, potentially compromising the planning process. Reference [5] investigates the optimal sizing of battery swapping stations, taking into account the dynamic loading patterns of electric vehicles. By analyzing the varying demand for charging, the study aims to optimize the capacity of battery swapping stations to efficiently meet fluctuating demand. However, it may not thoroughly integrate dynamic power distribution network reconfiguration or comprehensively address technical grid aspects, potentially resulting in suboptimal sizing decisions for battery swapping stations. Reference [6] addresses the challenges posed by uncertain loads in the optimal siting and sizing of battery swapping stations. The research explores methodologies to mitigate the impact of load variability on the performance and reliability of battery swapping infrastructure. However, it may not fully incorporate dynamic power distribution network reconfiguration or comprehensively address technical grid aspects, potentially limiting the robustness of the planning decisions. Reference [7] considers demand response mechanisms in determining the optimal placement and size of battery swapping stations.