The imperative of transitioning to sustainable energy practices to mitigate climate change necessitates the development of robust decision-support systems, with Building Performance Simulation (hereafter BPS) playing a central role. DesignBuilder (hereafter DB), a widely employed BPS tool, interfaces with the EnergyPlus dynamic thermal simulation engine, facilitating the analysis of energy consumption and generation based on the physical attributes of buildings, system configurations, and occupant behaviors. While DB offers significant utility in conducting optimization and prediction analyses to improve building performance, challenges persist regarding incorporating occupant behavior data due to complexity and privacy concerns, especially for residential buildings. Consequently, this paper investigated the impact of adding detailed residential occupant behaviors—namely heating schedules, heating temperature, and ventilation—on simulation accuracy using a residential house in the Netherlands as a case study. It revealed that adjusting heating schedules/hours has a more pronounced effect on simulation accuracy than the other two factors examined. These findings contribute to a nuanced understanding of the relationship between occupant behaviors and simulation accuracy, offering insights into data collection practices conducive to achieving acceptable levels of accuracy in BPS.