To enhance the adaptability of electric vehicle charging stations in low-temperature environments and alleviate pressure on distribution and road networks, a charging station planning model for low-temperature regions is proposed. A model for battery capacity and energy consumption under low temperatures is established based on the degradation mechanism of power batteries, allowing for more accurate simulation of driving conditions. By considering the driving, charging, and user decision characteristics of electric vehicles in low-temperature, a Monte Carlo sampling method is used to simulate the spatio-temporal distribution of charging demand for different vehicle types in low-temperature. A hybrid queuing theory is adopted to account for the impact of low-temperatures on charging efficiency, and a weighting function is introduced to minimize social costs, leading to optimal charging station location and capacity configurations. Simulation results demonstrate that the proposed model effectively balances the interests of road networks, distribution networks, and users based on the characteristics of low-temperature regions. It enables reasonable planning of electric vehicle charging stations in low-temperature regions, improving charging service satisfaction, reducing overall costs in cold environments, and enhancing the model's feasibility for practical application.