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In this paper, a model predictive control method is proposed to improve the performance on both temperature control and energy conservation for central air-conditioning system. Since the lack of consideration of the impact of cooling load can lead to a limitation on the energy saving effect, a cooling load model is proposed. Parameters in cooling load model, as well as the temperature model and energy consumption model are estimated. The optimal predictive controller is designed, and a chance constrained programming method is utilized to solve the optimal problem with stochastic parameters. Through a solution algorithm based on genetic algorithm, the control vector which can keep optimal in most uncertain cases can be acquired. The comparative results show the effectiveness of the proposed method.