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Ventilation system with thermal energy storage(TES)using phase change materials(PCMs)can be employed to save energy in buildings,which stores outdoor coldness in the PCMs at night and releases this energy to cool down the fresh ventilation air during the daytime.However,its performance depends on the design parameters.This paper presents a detailed parametric analysis to address the separate effect of each design parameter on the cooling energy supply and net electricity saving of the TES system against a conventional ventilation system for the climate of Beijing,by using a computational heat transfer model.A genetic algorithm(GA)is used to optimize the design parameters for maximizing the net electricity saving in four cities of China.The decision variables are related to the PCM melting temperature,PCM slab thickness and cold charging airflow rate.The results show that the saving-optimal solution is not unique and depends on the climate.GA optimization increases the net electricity saving by 10％–54％,with a mean value of 31％.Sensitivity analysis of net electricity saving to the above three variables is carried out.Likewise,the sensitivity of each variable is not unique and depends on the climate.