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China's urban rail transit is under rapid construction. Further improving the station environment and reducing the station operation energy consumption has become a key way to achieve high-quality development of rail transit. Among them, the ventilation system accounts for 17% of the total energy consumption of the metro environmental control system. In order to reduce the energy consumption of the fan at the end of the system while taking into account the air quality and comfort of the station, the air conditioning load of a subway station in Xi 'an was simulated and analyzed. The load prediction model was established, and the target air supply volume was calculated. The improved multi-objective sound search algorithm was used to optimize the hourly air supply volume. Through comparison and analysis with the traditional operation strategy, it is found that the temperature inside the station is significantly increased after optimization, and the temperature difference between the station and the outdoor is about 4 ℃, which meets the temporary thermal comfort needs of passengers in the station. Under the premise of maintaining the CO2 concentration in the station is lower than the healthy concentration limit, the energy saving rate of the ventilation system reaches 22.7%.