The Trombe wall is a typical passive building technique. To enhance the thermal performance of Trombe walls, a novel Trombe wall structure incorporating two phase change material (PCM) layers was designed. A numerical model of the PCM Trombe wall was established and validated against the experimental results. To explore the thermal performance of this PCM Trombe wall system, actual meteorological conditions were incorporated into the numerical simulations. Under transient conditions, the indoor temperature and velocity during the thermal storage and release stages were analyzed. Compared to conventional Trombe walls, the new PCM Trombe wall exhibited a 4 h delay in reaching peak temperature while simultaneously reducing indoor temperature fluctuations by 68.4%. Moreover, the new PCM Trombe wall showed excellent thermal storage capabilities, and the indoor temperature reached 18.2 °C after continuous cycles of thermal storage and release. Notably, the internal thermal storage layer in the new PCM Trombe wall can significantly reduce the indoor air velocity and improve thermal comfort.

Taking the high and large space of the University of Science and Technology Beijing Gymnasium as this research object, this paper analyzes the influence of different window positions, window-to-wall ratio (WWR), solar heat gain coefficient (SHGC), heat transfer coefficient (K), and visible light transmittance (VT) on the total indoor energy consumption in winter and summer and obtains the relationship between the daylight factor and VT formed when the window is opened per unit area. Through energy consumption simulation, the variation law and calculation formula for indoor total energy consumption are obtained. The results show that the SHGC and K of the exterior window have a significant influence on the total energy consumption. By using the energy consumption simulation of different types of exterior windows, it is concluded that the SHGC of the south-facing window is negatively correlated with the variation of air conditioning energy consumption per unit area Δe_1,w, while the others are positively correlated. Moreover, the SHGC and K of the skylight have the most significant influence on the Δe_1,w. The total energy consumption decreases and then increases with the increase in the window area, and there is a lowest point, so the right side of the lowest point is less than or equal to 105% of the lowest total energy consumption as a reasonable window area zone. Finally, a progressive optimization method for weighing daylighting and energy consumption in university gymnasiums in Beijing is proposed.