The development of adaptive building envelopes with advanced PCM to reduce building energy consumption is a promising topic. This study proposed an adaptive ventilation and sunlight regulation wall (AVSRW) by combining the variable transparency shape-stabilized PCM (VTSS-PCM), reflective film, and ventilation cavity. The combination of VTSS-PCM and reflective film could passively regulate the solar absorptivity (SA) of AVSRW. The ventilation cavity with airflow control enhanced the heat storage and release efficiency of VTSS-PCM. A dynamic photo-thermal coupling model of the AVSRW was presented and validated by a full-scale experiment in summer and winter conditions. Then, based on the weather data of the typical meteorological year of Changsha, China, the performances of AVSRW on days, months, and a year were evaluated. The impact of three influential factors and their combined effects on the performance of AVSRW were analyzed. Ultimately, a global optimization was conducted to improve the performance of AVSRW, and compared with the massive wall. The results showed that the AVSRW passively decreased its SA on summer days and increased its SA on winter days. The total annual undesired heat exchange (TAHE) of AVSRW first decreased and then increased with the increase of melting temperature (Tm) and thickness (L) of VTSS-PCM. The reflective film had an opposite effect on the annual heat gain (AHG) and annual heat loss (AHL) of AVSRW, resulting in the TAHE remaining unchanged with the increase of reflectivity (R) of the reflective film. The greater the L, the smaller effect of the Tm and R on the AHG and AHL, and the greater the R, the greater effect of the Tm and L on the AHG and AHL. After optimization, the values of the Tm, L, and R corresponding to the optimal solution were 24.60 °C, 0.17 m, and 0.63, respectively. Compared with the reference wall, the AVSRW with the best performance had lower AHG and AHL, and the annual energy-saving rate of the AVSRW reached 43.49%. This study guides the application and parameter optimization of AVSRW in hot summer and cold winter regions.