With the continuous expansion of subway scale and energy consumption, energy-saving ventilation and air-conditioning (VAC) systems in subway stations have gradually become a research focus. In this study, the influential parameters of the VAC energy model in subway stations are identified and ranked using three commonly used sensitivity analysis methods (regression-based, screening-based, and variance-based). The results show that the top 25% ranked parameters identified by the three methods are the same, but the orders are different. Among the three sensitivity analysis methods, the rankings of the variance- and screening-based methods are basically the same, whereas the ranking of the regression-based method is quite different from the previous two. In addition, the regression method is the most efficient method considering the computational cost, and the calculation times of the variance- and screening-based methods are 25 and 3 times, respectively. By comparison, it can be concluded that the screening-based method performs best in terms of parameter ranking and computational cost. Furthermore, the quantitative influence of the above-mentioned parameters on the energy consumed by the VAC system in a typical island subway station was studied. The results show that the impact of outdoor air parameters is as high as 84%, the effects of the mechanical fresh air volume, air infiltration volume through the entrances, and air infiltration volume through the platform screen doors are 43%, 29%, and 12%, respectively; the impact of equipment efficiency reaches 39% and is non-linear. The influence of the air parameters inside the station and the tunnel is 37% and 33%, respectively. Ultimately, the outcome of this research points out important variables that must be underlined in the energy conservation design and operation of subway stations, providing guidance for energy-saving operations and the management of stations.