The easiest way to improve energy efficiency and thermal comfort in existing buildings is to adjust setpoints. However, although Chinese standards regulated the heating and cooling setpoints for different climate zones in China, they lacked consideration for occupants’ thermal comfort and ignored the ventilation setpoints. Therefore, this study aimed to identify optimal heating, cooling, and ventilation setpoints at the design stage to enhance building energy performance and indoor thermal comfort in Chinese residential buildings. This study used DesignBuilder to simulate the energy usage and thermal comfort with different setpoints and judged which combination was the best. To conduct this study across the whole of China, the typical cities in different climate zones were selected by using machine learning. Results indicated that adjusting setpoints in Harbin, Beijing, and Shanghai could increase comfortable days by 43.95 %, 54.23 %, and 23.36 % respectively, with minimal impact on energy usage. In Guangzhou, energy usage could be reduced by 7.56 % with a 5.91 % decrease in comfortable days, while Kunming could see an 11.11 % increase in comfortable days with a 5.92 % rise in energy consumption. Additionally, sensitivity analysis revealed that activity template variation was most critical for energy usage in Harbin, Beijing and equipment power density variation was most important for thermal comfort in Shanghai, Guangzhou, and Kunming. Furthermore, proposed setpoint combinations demonstrated resilience to future weather conditions in most typical cities, except for Guangzhou. These findings provide valuable insights for designers and researchers aiming to retrofit residential buildings, emphasizing the importance of considering both energy efficiency and occupant comfort. This study introduces innovative approaches like comprehensive setpoint optimization and machine learning for typical city selection, providing practical solutions to improve energy efficiency and thermal comfort in residential buildings.