Abstract: This paper proposed an energy-saving control model for metro stations based on optimal control method to address the issue of high energy consumption in air conditioning and ventilation systems, used the measured data of the energy management system of a metro station in Xiamen City, and constructed the energy consumption model of the air conditioning and ventilation system of the metro station with the help of the Transient System Simulation (TRNSYS) Program. Based on this, the paper proposed an optimal control method based on multi-objective optimization problem, that was, establishing the energy consumption cost function and temperature error cost function of the optimization problem, using the steepest descent method to obtain the optimal solution, and then using particle swarm optimization algorithm to verify the global optimality of the solution. The experimental results show that compared with fixed frequency control and Particle Swarm Optimization (PSO) improved PID (Proportional Integral Derivative) control, the optimal control method improves response speed, reduces adjustment time, lowers steady-state error, and increases energy savings by 38.68% and 8.1%, respectively. This paper optimizes the calculation of the global optimal control matrix to achieve dynamic matching of cooling load in the air conditioning and ventilation system, achieving the goal of reducing temperature deviation and total energy consumption of the air conditioning and ventilation system, and improving the control performance and economy of the energy-saving control system.